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Keywords Stochastic programming; Scenario tree generation; Recursive algorithms; Model error; Distributionally robust solutions HIGHLIGHTS * This is an elaboration of the semiplenary talk I held in Athens at EURO 2021. * The paper summarizes some earlier work, a new aspect is however included by emphasizing the recursive structure of data structures and algorithms. * The role of the ambiguity radius as a tradeoff between model information and efficiency of the optimal decisions is elaborated for several informative examples. Abstract Stochastic multistage decision problems appear in many - if not all - application areas of Operations Research. While to define such problems is easy, to solve them is quite difficult, since they are of infinite dimension. Numerical solution can only be found by solving an approximate, easier problem. In this paper, we show good approximations can be found, where we emphasize the recursive structure of the involved algorithms and data structures. In a second part, the problem of coping with the model error of approximations is discussed. We present algorithms for finding distributionally robust solutions for the model error problem. We also review some application cases of such situations from the literature. Author Affiliation: Faculty of Economics and Statistics, University of Vienna, Wien Oskar-Morgenstern Platz, Vienna A-1090, Austria Article History: Received 6 December 2021; Revised 20 March 2022; Accepted 2 April 2022 (footnote)[white star] This paper is an elaboration of a semiplenary talk held at the EURO21 conference in Athens Byline: Georg Ch. Pflug [georg.pflug@univie.ac.at]

Keywords OR in health services; Implementation Abstract This paper is based on the keynote address given by the paper's first author at EURO 2021. We draw on our experience over more than three decades to define the critical challenges of healthcare implementation. We do not address issues pertaining to technical quality of a solution. Rather, we focus on five general characteristics of the problem that should be carefully considered for any healthcare project that requires implementation. The problem needs an internal Champion; there should be a current Critical Issue; one must understand and adapt to the Cultural dynamics of the organization; appropriate Data exists; and we need to manage Expectations. We illustrate each with examples of our successes, failures, and mixed results. Finally, we summarize what short and long-term steps we believe the operational research community can take that will lead to improvement in each of these areas. Author Affiliation: Department of Mechanical & Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, ON, M5S 3G8, Canada * Corresponding author. Article History: Received 30 November 2021; Revised 11 April 2022; Accepted 16 April 2022 Byline: Michael W. Carter [mike.carter@utoronto.ca] (*), Carolyn R. Busby

Keywords Multiple objective programming; ESG in investing; Efficient frontiers; ESG integration; Tri-criterion portfolio selection Highlights * The paper provides a framework for solving the three-objective Markowitz problem where sustainability in the form of ESG is the third objective. * With no clear definition of ESG integration in the literature, we provide a crisp definition of what it is and is not. * A new technique called non-contour efficient fronts is presented for searching tri-criterion efficient surfaces for most preferred portfolios. * While current methods leave ESG on the table, the non-contour methodology leads to portfolios with significantly greater ESG content. * We develop an ESG integration index that is able to assess the degree to which ESG has been integrated into a portfolio. Abstract The paper focuses on investors whose strength of interest in sustainability issues (such as environmental, social, and governance) causes ESG to become a third criterion alongside risk and return in portfolio selection. This causes the efficient frontier to become an efficient surface. This means that an investor's optimal portfolio is no longer the point of most preferred risk/return tradeoff on the mean-variance (M-V) efficient frontier, but is the point of most preferred risk/return/ESG tradeoff on the investor's M-V-ESG efficient surface. However, to find such a point requires non-trivial ESG integration which is the name given to the process of integrating ESG into the portfolio construction process after screening. With the third objective transporting the problem into 3D-space, it is difficult to search the efficient surface in any kind of comprehensive fashion using M-V based or other bi-criterion techniques as this is akin to a 2-dimensional being trying to view a 3-dimensional object. To remedy the situation, the paper proposes a tri-criterion approach that computes efficient surfaces and special non-contour curves (called NC-efficient fronts in the paper) that are stretched across the efficient surface so as to dragnet it for the points of best ESG integration within it. Using the methodology and data from the S&P500, the paper conducts computational tests on problems with up to 500 securities and under different constraint conditions so as to know what to expect from the new approach over a range of situations. Author Affiliation: (a) University of Georgia, Department of Finance, Athens, Georgia 30602, USA (b) University of Augsburg, Faculty of Business Administration and Economics and Centre for Climate Resilience, Universitaetsstrasse 12, 86159 Augsburg, Germany * Corresponding author. Article History: Received 30 November 2021; Accepted 5 August 2022 Byline: Ralph E. Steuer [rsteuer@uga.edu] (*,a), Sebastian Utz [sebastian.utz@uni-a.de] (b)

Keywords Behavioural or; System dynamics; Intervention Highlights * Critically evaluates the 'behavioural turn' in OR and re-visits the core ideas. * Applies to system dynamics the behavioural perspective of biases and deviations from rationality. * Presents a new framework for system dynamics studies which reveals a range of behavioural effects. * Proposes five 'Behavioural SD' axioms involving interdisciplinarity and experiments. * Makes the case that 'Behavioural SD' can explain behavioural phenomena and improve model-based interventions. Abstract Attempts to examine so-called 'behavioural effects' have reached into many different fields and are in full sway across OR. This paper considers whether this can be applied to System Dynamics modelling in a useful way. The idea is that humans frequently do not employ strict rationality in their daily lives but make errors and are subject to fallacies. This can shed light on the cognitive and human interaction aspects of the process and outcomes of modelling. The paper first raises concerns about the current state of 'Behavioural OR' -- BOR. To refocus the underlying ideas it then returns to the Decision Theory roots, takes a broader view using an illustration from the history of science and then builds on work which first proposed a link to System Dynamics (SD). The core of the paper then explores in depth how behavioural ideas apply to SD. This is done using examples dealing with complex systems in a 'naïve' versus a 'sophisticated' way, and then using a mind map. It then offers a new and detailed framework of the stages of an SD-based intervention, indicating the presence of behavioural effects and providing a fine-grained discussion of those effects as they apply to SD. It builds on this by proposing a definition of 'Behavioural System Dynamics' (BehSD) in terms of its perspective on phenomena, five new, constitutive axioms, and its potential for improving practice. The paper closes by reprising the nature and potential of 'BehSD' and by sketching how research that adopts this perspective might go forward. Author Affiliation: (a) Henley Business School, University of Reading, Reading, RG6 6UD, United Kingdom (b) Institute for Management Research, Radboud University, P.O. Box 9108, 6500, HK, Nijmegen, The Netherlands * Corresponding author. Article History: Received 18 November 2020; Accepted 12 August 2022 Byline: David C. Lane (a), Etiënne A.J.A. Rouwette [Etienne.Rouwette@ru.nl] (b,*)

Keywords Data envelopment analysis; Corporate social responsibility; Dynamic data envelopment analysis; Fuzzy data envelopment analysis Highlights * A new method for inefficiency evaluation is proposed. * The method accounts for firms' CSR activities. * The method considers the vagueness of CSR data through fuzzy DEA. * The method allows for dynamics of firms' production decisions through adjustment costs. * Dynamic fuzzy methodology adds some value to the standard crisp approach. Abstract This paper contributes to research on the corporate social responsibility (CSR) field and the inefficiency measurement of firms by proposing a new method for evaluating inefficiency accounting for firms' CSR activities. The new approach considers the imprecise nature of CSR data through the fuzzy data envelopment analysis (FDEA) method and further extends it by allowing for the dynamic interdependence of firms' production decisions through adjustment costs, related to firms investments. In addition, the new method deals with zero or negative values for inputs and/or outputs of the data. The empirical application used in this paper considers a dataset of CSR activities of European firms for three industries (capital, consumption, and other) over the period 2014--2016. Two main results are found with this data. First, the study shows that fuzzy dynamic inefficiencies tend to be lower than these obtained from the conventional crisp evaluation of inefficiency. Second, the study finds some differences in dynamic inefficiencies at distinct levels of fuzziness. Overall, the results seem to confirm that the usage of dynamic fuzzy methodology adds some value to the standard crisp approach. Author Affiliation: (a) Center of Operations Research (CIO), Miguel Hernandez University of Elche (UMH), Elche, Alicante, Spain (b) Department of Logistics, Wroclaw University of Economics and Business, ul. Komandorska 118/120, Wroclaw 53-345, Poland * Corresponding author. Article History: Received 1 February 2021; Accepted 4 September 2022 Byline: Juan Aparicio (a), Magdalena Kapelko [magdalena.kapelko@ue.wroc.pl] (b,*), Lidia Ortiz (a)

Keywords OR in environment and climate change; Multistage distributionally robust optimization; Phi-divergences; Water resources; Nested benders decomposition Highlights * Multistage distributionally robust optimization (MDRO) with [phi]-divergences is studied. * A nested Benders decomposition algorithm is proposed and its properties are examined. * The approach is applied to allocate water under climate uncertainties in Tucson, AZ. * Water allocation and infrastructure planning via MDRO helps reduce extreme shortages. Abstract This paper investigates a Multistage Distributionally Robust Optimization (MDRO) approach to water allocation under climate uncertainty. The MDRO is formed by creating sets of conditional distributions (called conditional ambiguity sets) on a finite scenario tree. The distributions in the conditional ambiguity sets remain close to a nominal conditional distribution according a [phi]-divergence (e.g., Kullback-Leibler divergence, Hellinger distance, Burg entropy, etc.). The paper discusses a decomposition algorithm to solve the resulting MDRO with [phi]-divergences, which uses the dual formulation and solves only linear subproblems instead of convex ones. Some properties of the algorithm such as generating feasible policies and valid upper/lower bounds are established. The paper then applies the modeling and solution techniques to allocate water in a rapidly-developing area of Tucson, Arizona. Tucson, like many arid and semi-arid regions around the world, faces considerable uncertainty in its ability to provide water for its citizens in the future. The primary sources of uncertainty in the Tucson region include (1) unpredictable population growth, (2) the availability of water from the Colorado River, and (3) the effects of climate variability on water consumption. This paper integrates forecasts for all these sources of uncertainty into a single optimization model for robust and sustainable water allocation. Then, it uses this model to analyze the value of constructing additional treatment facilities to reduce future water shortages. The results indicate that the MDRO approach can be very valuable for water managers by providing insights to minimize their risks and help them plan for the future. Author Affiliation: (a) Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720, USA (b) Department of Integrated Systems Engineering, The Ohio State University, Columbus OH 43210, USA * Corresponding author. Article History: Received 21 November 2019; Accepted 24 June 2022 Byline: Jangho Park [janghopark.1814@gmail.com] (a), Güzin Bayraksan [bayraksan.1@osu.edu] (*,b)

Keywords Logistics; Sorting operations; Express parcel delivery; Robust optimization Highlights * We introduce robust optimization models for express parcel sort planning. * We explicitly model demand uncertainty in arrival quantities and arrival times. * We demonstrate models' computational viability on instances using industry data. * We show models' value in generating plans trading-off sorting cost and robustness. Abstract Parcel logistics services play a vital and growing role in economies worldwide, with customers demanding faster delivery of nearly everything to their homes. To move larger volumes more cost effectively, express carriers use sort technologies to consolidate parcels that share similar geographic and service characteristics for reduced per-unit handling and transportation costs. This paper focuses on an operational planning problem that arises in two-stage sort systems operating within parcel transportation networks. In this context, primary sorters perform an initial grouping of parcels into 'piles' that are subsequently dispatched when necessary to secondary sorters; there, each pile's parcels are fine-sorted based on their final destinations and service class for packing into outbound transportation vehicles. Such systems must be designed to handle a high degree of uncertainty in the quantity and timing of arriving parcels, yet must also group and sort the parcels to meet tight departure deadlines. Thus motivated, this paper presents robust planning models that assign parcels to sort equipment while protecting against different sources of demand uncertainty commonly faced by parcel carriers. We demonstrate the computational viability of the proposed models using realistic-sized instances based on industry data, and show their value in providing sort plan alternatives that trade off operational costs and levels of robustness. Author Affiliation: H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA * Corresponding author. Article History: Received 15 March 2021; Accepted 13 July 2022 Byline: Reem Khir [reem.khir@gatech.edu] (*), Alan Erera, Alejandro Toriello

Keywords Logistics; Pickup and delivery; Transshipments; Time windows; Mixed-integer linear programming Highlights * This paper addresses the pickup and delivery problem with transshipments (PDP-T) and the pickup and delivery problem with time windows and transshipments (PDPTW-T). * We make revisions and modifications to two state-of-the-art models. * We present a new model and generate several benchmarks for future comparison. * The solvable scale is increased significantly by using the new model. * Computational time is reduced by 96% and 40% for PDP-T and PDPTW-T, respectively. Abstract The pickup and delivery problem with transshipments (PDP-T) is generalized from the classical pickup and delivery problem (PDP) by allowing the transfer of requests between vehicles. After considering the time window constraints, the PDP-T is further generalized to the pickup and delivery problem with time windows and transshipments (PDPTW-T). In this paper, we review two state-of-the-art models for the PDP-T and PDPTW-T. We point out the possible issues existing in the models and provide our revisions. In addition, we develop a new mixed-integer linear programming formulation to solve the PDP-T and PDPTW-T. The performance of the proposed model is evaluated by solving 340 generated PDP-T instances and 360 open-access PDPTW-T instances. Computational results show that the proposed model outperforms the existing models in terms of solution quality and computing time. PTP-T instances with up to 25 requests and 2 transfer stations are solved to optimality by using the proposed model. As a comparison, the best-known benchmarks in the literature are instances with 5 requests and 1 transfer station. In addition, the computing time is significantly reduced. In our experiments, the average computational time for solving PDP-T is reduced by 96%. For PDPTW-T instances, the solvable scale is increased from 3 requests and 4 transfer stations to 5 requests and 4 transfer stations. The average computing time is reduced by 40%. Author Affiliation: Department of Industrial and Systems Engineering, The University of Tennessee, Knoxville, Knoxville, TN 37996, United States * Corresponding author. Article History: Received 16 September 2021; Accepted 31 May 2022 Byline: Zefeng Lyu, Andrew Junfang Yu [ajyu@utk.edu] (*)

Keywords Supply chain management; Private labels; National brands; e-tailer; Sourcing strategy Highlights * This paper fills a research gap by thoroughly studying whether an e-tailer should introduce a private label (PL) product. * If yes, when should the e-tailer manufacture it in-house or outsource if from a national brand (NB) or another third-party manufacturer? * It shows the e-tailer would charge the highest agency fee and provide the highest service level when sourcing from the NB manufacturer * It shows that there is always a sourcing strategy that can benefit the NB manufacturer and the e-tailer. * It shows the robustness of the analytic findings by considering model extensions. Abstract Many electronic retailers (e-tailers) have introduced private labels (PLs). Although there is a vast literature on modeling pricing and e-tailers' operational issues, research on PL sourcing has been lacking. This paper seeks to fill this gap by investigating an e-tailer (she) who can manufacture her PL in-house or source it from an external third-party manufacturer or a national brand manufacturer (he). The e-tailer simultaneously sells the PL directly and the product of the national brand (NB) manufacturer with agency selling. Furthermore, she provides consumer service for both products. Our analysis leads to the following major results. First, the e-tailer would charge the highest agency fee and provide the highest service level when sourcing from the NB manufacturer. Second, the PL sourcing preference of the e-tailer mainly depends on the production cost and consumer service sensitivity. In contrast, the profit of the NB manufacturer is influenced primarily by the consumer preference for PL and the sourcing strategy of the e-tailer. Third, there is always a PL sourcing strategy that can benefit the NB manufacturer and the e-tailer. Our model extensions explore how price elasticity, product quality, consumer loyalty, and exogenous fees affect our main results, which are shown to be robust. Author Affiliation: (a) School of Economic and Management, University of Electronic Science and Technology of China, China (b) School of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, China (c) Lazaridis School of Business and Economics, Wilfrid Laurier University, Canada * Corresponding author. Article History: Received 8 November 2021; Accepted 12 May 2022 Byline: Hengyu Li (a), Huangen Chen (b), Junwu Chai [chaijw@uestc.edu.cn] (a,*), Victor Shi (c)

Keywords Data envelopment analysis; Business partnerships; Inverse DEA; Strategic alliances; Decision making units Highlights * Defines various types of strategic alliances and partnerships between different decision making units. * Develops novel data envelopment analysis models for business partnerships. * Guides partners on how redistributing inputs and outputs could improve their efficiency score. * Helps partners to use each other's resources in order to reach target efficiency. Abstract Strategic alliances and partnerships including mergers and acquisitions have been a growing trend in many industries in the past decades. There are many studies in the literature emphasizing the importance of business partnerships. However, literature on partnership optimization is quite limited. This paper defines various types of strategic alliance collaborations and partnerships between different decision making units (DMUs) and develops data envelopment analysis (DEA) models to guide partners on how redistributing their inputs and outputs could enhance their performance. The results of this study are useful for companies considering strategic alliances and partnerships to improve competitiveness. An application in banking is used to highlight the advantages of the proposed method in this paper. Author Affiliation: Faculty of Business, University of New Brunswick, Saint John NB E2K 5E2, Canada * Corresponding author. Article History: Received 30 October 2021; Accepted 17 May 2022 (miscellaneous) Edited by Prof. Mike Yearworth Byline: Gholam R. Amin [gamin@unb.ca] (*), Mustapha Ibn Boamah [mboamah@unb.ca]

Keywords Data envelopment analysis; Meta-frontier; Technology gap; Technology switcher; Technology club Highlights * We extend the concept of meta-frontier when technology switchers are considered. * We quantify the impacts of the switchers on inefficient behavior and technology gap. * We define the concepts of efficiency and technology gap switcher effects. * The number of technologies can change over time. * We provide an application to technology clubs using country data. Abstract The concept of meta-frontier has been proposed in order to deal with group heterogeneity among entities for nonparametric efficiency analysis. In brief, the meta-frontier is defined as the envelopment of the group-specific frontiers and naturally allows one to distinguish inefficiency from technology gap. While this concept has demonstrated its usefulness for empirical studies and been extended in several directions, two major shortcomings are the fixed number of groups and the static allocation of entities across groups. This is particularly problematic when dealing with panel data. In this paper, we extend the meta-frontier approach when technology switchers are considered, and quantify the impacts of the switchers on inefficient behavior and technology gap. We demonstrate the usefulness of our new methodology with the case of the technology clubs in the world economy. Author Affiliation: HEC Liège, Université de Liège, Belgium Article History: Received 28 December 2020; Accepted 19 May 2022 (footnote)[white star] We thank the Editor Robert Graham Dyson and the three anonymous referees for their comments that substantially improved the paper. Byline: Barnabé Walheer [barnabe.walheer@uliege.be]

Keywords Vehicle routing problem; Informative path planning; Orienteering problem; Covering tour problem; Close-enough vehicle routing Highlights * This paper introduces a unified definition of the concept of spatial coverage in routing and path planning and introduces a categorization scheme of related problems. * Unified mathematical models highlight similarities and show differences between models developed in different communities such as Robotics and Operations Research. * The overview simplifies the search for similar problems and suitable modeling variants and solution methods and bridges the gap between disciplines. Abstract Routing and path planning problems that involve spatial coverage have received increasing attention in recent years in different application areas. Spatial coverage refers to the possibility of considering nodes that are not directly served by a vehicle as visited for the purpose of the objective function or constraints. Despite similarities between the underlying problems, solution approaches have been developed in different disciplines independently, leading to different terminologies and solution techniques. This paper proposes a unified view of the approaches: Based on a formal introduction of the concept of spatial coverage in vehicle routing, it presents a classification scheme for core problem features and summarizes problem variants and solution concepts developed in the domains of operations research and robotics. The connections between these related problem classes offer insights into common underlying structures and open possibilities for developing new applications and algorithms. Author Affiliation: (a) FZI Research Center for Information Technology, Haid-und-Neu-Str. 10-14, Karlsruhe D-76131, Germany (b) TU Dortmund University, Leonhard-Euler-Straße 5, Dortmund D-44227, Germany * Corresponding author. Article History: Received 15 July 2021; Accepted 13 February 2022 (footnote)1 ORCID: https://orcid.org/0000-0003-0670-6269 (footnote)2 ORCID: https://orcid.org/0000-0001-6380-1348 Byline: Katharina Glock [kglock@fzi.de] (1,a), Anne Meyer [anne2.meyer@tu-dortmund.de] (*,2,b)

Keywords Game theory; Simple games; Set-weighted games; Cover problem; Cooperative generating functions Highlights * A decomposition theorem of set-weighted games is proved. * Set-weighted games class is closed under the operations of union and intersection. * Cooperative generating functions for power indices are found. Abstract The cover of a transport, social, or communication network is a computationally complex problem. To deal with it, this paper introduces a special class of simple games in which the set of minimal winning coalitions coincides with the set of least covers. A distinctive feature of such a game is that it has a weighted form, in which weights and quota are sets rather than real numbers. This game class is termed set-weighted games. A real-life network has a large number of least covers, therefore this paper develops methods for analyzing set-weighted games in which the weighted form is taken into account. The necessary and sufficient conditions for a simple game to be a set-weighted game were found. The vertex cover game (Gusev, 2020) was shown to belong to the set-weighted game class, and its weighted form was found. The set-weighted game class has proven to be closed under operations of union and intersection, which is not the case for weighted games. The sample object is the transport network of a district in Petrozavodsk, Russia. A method is suggested for efficiently deploying surveillance cameras at crossroads so that all transport network covers are taken into account. Author Affiliation: HSE University, Russian Federation Article History: Received 16 November 2021; Accepted 13 May 2022 Byline: Vasily V. Gusev [vgusev@hse.ru]

Keywords Combinatorial optimization; Discounted knapsack problem; Fixation; Dynamic programming; Instance generator Highlights * Heuristic and exact fixation rules are introduced to strengthen dynamic programming. * Instances from the literature are solved by the proposed approach very easily. * Harder instances for exact methods are generated to justify the use of heuristic. Abstract In this paper we consider the discounted 0--1 knapsack problem (DKP), which is an extension of the classical knapsack problem where a set of items is decomposed into groups of three items. At most one item can be chosen from each group and the aim is to maximize the total profit of the selected items while respecting the knapsack capacity constraint. The DKP is a relatively recent problem in the literature. It was considered in several recent works where metaheuristics are implemented to solve instances from the literature. In this paper we propose a two-phase approach in which the problem is reduced by applying exact and / or heuristic fixation rules in a first phase that can be viewed as a preprocessing phase. The remaining problem can then be solved by dynamic programming. Experiments performed on available instances in the literature show that the fixation techniques are very useful to solve these instances. Indeed, the preprocessing phase greatly reduces the size of these instances, leading to a significant reduction in the time required for dynamic programming to provide an optimal solution. Then, we generate a new set of instances that are more difficult to solve by exact methods. The hardness of these instances is confirmed experimentally by considering both the use of CPLEX solver and our approach. Author Affiliation: (a) Univ. Polytechnique Hauts-de-France, LAMIH, CNRS, UMR 8201, Valenciennes F-59313, France (b) INSA Hauts-de-France, Valenciennes F-59313, France * Corresponding author. Article History: Received 7 March 2021; Accepted 22 April 2022 (footnote)1 'Professeur émérite' - Now retired. Byline: Christophe Wilbaut [christophe.wilbaut@uphf.fr] (*,a,b), Raca Todosijevic [raca.todosijevic@uphf.fr] (a,b), Saïd Hanafi [said.hanafi@uphf.fr] (a,b), Arnaud Fréville (1,a)

Keywords Queueing; Active queue management; Random early detection; Renovation Highlights * Renovation with delay can achieve goals common for traditional AQMs. * In single-server queues delayed renovation can show similar performance as RED-type AQMs. * Too large regular delay threshold diminishes the potential of the renovation. Abstract This paper is devoted to the performance evaluation of the finite--capacity single-server queue with Poisson input and general service times, which is equipped with the novel queue-control mechanism -- called renovation with delay. Renovation implies that each customer, when leaving the system upon its service completion, may also remove customers waiting in the queue. The number of customers to be removed is selected each time independently of the previous decisions and probabilistically based on the given probability distribution. The renovation with the delay considered in this paper means that the system must accumulate the (known) fixed number of service completions before the next renovation can be triggered. First in the literature numerical evidence is given, that the long-run performance of the system with such delayed renovation mechanism can be similar to that of the systems with the well-known active queue management mechanisms such as random early detection, at least in its basic version. The key stationary performance characteristics reported are the loss probability and the mean number of customers in the system. The unified analytical framework for the computation of the key performance characteristics, which is of independent interest, is also developed. Author Affiliation: Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation * Corresponding author. Article History: Received 28 October 2020; Accepted 28 May 2022 Byline: Mikhail Konovalov [mkonovalov@ipiran.ru], Rostislav Razumchik [rrazumchik@ipiran.ru] (*)

Keywords Validation of OR computations; Maximum flow; Instance space analysis; Instance selection; Feature selection Highlights * Six key features of instances capture behaviors of popular maxflow algorithms; * Instance Space Analysis reveals regions of algorithm strength and weakness; * Representation bias via oversampling is mitigated by an instance selection procedure; * Selected maxflow instances are diverse and unbiased to study algorithm performance; * Resulting insights reveal impact of arc/path finding strategies on algorithm success. Abstract The Maximum Flow Problem (MFP) is a fundamental network flow theory problem, for which many algorithms, supported by strong theoretical worst-case analyses, have been proposed. However, their practical efficiency depends on the network structure, making it unclear which algorithm is best for a particular instance or a class of MFP. Instance Space Analysis (ISA) is a methodology that provides insights into such per-instance analysis. In this paper, the instance space of MFP is constructed and analysed for the first time. Novel features from the networks are extracted, capturing the performance of MFP algorithms. Additionally, this paper expands the ISA methodology by addressing the issue of how benchmark instances should be selected to reduce bias in the analysis. Using the enhanced ISA methodology with MFP as the case study, this paper demonstrates that the most important features can be detected, and machine learning methods can identify their impact on algorithm performance, whilst reducing the bias caused by over-representation within the selected sample of test instances. The enhanced methodology enables new insights into the performance of state-of-the-art general purpose MFP algorithms, as well as recommendations for the construction of comprehensive and unbiased benchmark test suites for MFP algorithm testing. Author Affiliation: School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC 3010, Australia * Corresponding author. Article History: Received 14 June 2021; Accepted 9 April 2022 Byline: Hossein Alipour [h.alipour@unimelb.edu.au] (*), Mario Andrés Muñoz [munoz.m@unimelb.edu.au], Kate Smith-Miles [smith-miles@unimelb.edu.au]

Keywords Decision analysis; Ride-sharing; Sustainability; Service supply chain; Pareto front Highlights * Study a sustainability-oriented operational model for online ride-sharing platforms. * Develop a multi-objective model considers indicators of the triple-bottom-line. * Propose an effective method to generate the Pareto front efficiently. * Study the correlation among different objectives and analyse their variation trends. Abstract By directly connecting passengers and private transportation service providers, online ride-sharing platforms reduce the number of intermediaries and improve the utilization of transportation resources. In addition to economic benefits, ride-sharing could provide environmental and social advantages. This paper studies a sustainability-oriented operational model for online ride-sharing platforms. We develop a holistic multi-objective mathematical model considering important indicators of the triple-bottom-line and examine its effects on the dispatching strategy. An effective method has been introduced to solve the model, as well as an approach to efficiently generate the Pareto front. Moreover, we validate the model and the solution methods through an extensive case study with different scenarios based on large-scale real-world data. We study the correlation among the objectives and analyse their variation trends when adjusting the influential factors. Finally, in this paper, useful managerial insights are provided for decision-makers of the platforms, such as how to balance the triple-bottom-line in a smart way. Author Affiliation: (a) School of Science, Zhejiang University of Science and Technology, Hangzhou 310023, China (b) School of Economics and Management, Beihang University, Beijing 100191, China (c) College of Business and Economics, UAE University, Al Ain, United Arab Emirates (d) Univ. Artois, UR 3926, Laboratoire de Génie Informatique et d'Automatique de l'Artois (LGI2A), F-62400 Béthune, France * Corresponding author. Article History: Received 3 August 2021; Accepted 22 April 2022 Byline: Yuhan Guo [yuhan.guo@zust.edu.cn] (a,*), Yu Zhang (b), Youssef Boulaksil (c), Yaguan Qian (a), Hamid Allaoui (d)

Keywords Pandemic; Operational research; Epidemic; Outbreak; SARS-CoV-2 Abstract In this special issue, 23 research papers are published focusing on COVID-19 and operational research solution techniques. First, we detail the process from advertising the call for papers to the point where the best papers are accepted. Then, we provide a summary of each paper focusing on applications, solution techniques and insights for practitioners and policy makers. To provide a holistic view for readers, we have clustered the papers into different groups: transmission, propagation and forecasting, non-pharmaceutical intervention, healthcare network configuration, healthcare resource allocation, hospital operations, vaccine and testing kits, and production and manufacturing. Then, we introduce other possible subjects that can be considered for future research. Author Affiliation: (a) Rennes School of Business, 2 rue Robert d'Arbrissel, Rennes, 35065 France (b) Grupo de Sistemas de Optimización Aplicada, Instituto Tecnológico de Informática, Ciudad Politécnica de la Innovación, Edifico 8 G, Acc. B. Universitat Politècnica de València, Camino de Vera s/n, València, 46021, Spain (c) INSEAD Technology and Operations Management Area, Blvd de Constance, Fontainebleau, 77305 France * Corresponding author. Article History: Received 3 July 2022; Accepted 4 July 2022 Byline: Reza Zanjirani Farahani [reza.zanjirani-farahani@rennes-sb.com] (a,*), Rubén Ruiz (b), Luk N. Van Wassenhove (c)

Keywords Supply chain management; Risk mitigation; Network Data Envelopment Analysis Highlights * This paper constructs a network data envelopment analysis (NDEA) model to assess risk mitigation investments. Abstract Supply chain risk mitigation involves investing in strategic activities that minimize the financial impact of disruptions to the flow of goods in a supply chain. However, methods for assessing these strategies are not well established. Given the importance of mitigating supply chain risk, having a quantitative method for evaluating risk mitigation is imperative. This paper constructs a network data envelopment analysis (NDEA) model to assess risk mitigation investments by considering the cost of the strategies, performance outcomes, and interdependencies among the different stages of the supply chain. Risk mitigation strategies in this study were measured at the supplier, manufacturing, and customer segments of a firm's supply chain. Efficiency analysis (comparing NDEA to traditional approaches) shows that NDEA provides a more holistic and useful assessment of supply chain risk mitigation performance. Author Affiliation: (a) School of Management, University at Buffalo, 325 Jacobs Hall, Buffalo, NY 14260, United States (b) Eli Broad Graduate School of Management, Michigan State University, East Lansing, MI 48824, United States * Corresponding author. Article History: Received 12 October 2020; Accepted 9 March 2022 (footnote)1 *Equal contribution by the second and third authors Byline: Richard Kraude [rlkraude@buffalo.edu] (a,*), Sriram Narayanan [narayanan@broad.msu.edu] (b), Srinivas Talluri [talluri@broad.msu.edu] (b,1)

Keywords Risk management; Optimal reinsurance; Distortion risk measure; Vajda condition; Backward-forward optimization Highlights * This paper studies the Vajda condition in optimal reinsurance contract design. * Via a quantile formulation, this paper proposes a backward-forward method. * For a variety of problems, this method is applicable to derive solutions. * Special cases with distortion risk measures are worked out. * An empirical illustration is provided with Danish fire insurance losses. Abstract To manage the risk of insurance companies, a reinsurance transaction is among the myriad risk management mechanisms the top ranked choice. In this paper, we study the design of optimal reinsurance contracts within a risk measure minimization framework and subject to the Vajda condition. The Vajda condition requires the reinsurer to take an increasing proportion of the loss when it increases and therefore imposes constraints on the indemnity function. The distortion-risk-measure-based objective function is very generic, and allows for, for example, an objective to minimize the risk-adjusted value of the insurer's liability, and for heterogeneous beliefs regarding the loss distribution by the insurer and reinsurer. Under a mild condition, we propose a backward-forward optimization method that is based on a marginal indemnity function formulation. To show the applicability and simplicity of our strategy, we provide three concrete examples with the Value-at-Risk: one with the risk-adjusted value of the insurer's liability, one with an objective function that follows from imposing Pareto optimality, and one with heterogeneous beliefs. We conclude this paper with an empirical application with Danish fire insurance losses and the Value-at-Risk and the Tail Value-at-Risk. Author Affiliation: (a) Amsterdam School of Economics, University of Amsterdam, Amsterdam, 1001 NJ Amsterdam, the Netherlands (b) Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta T2N 1N4, Canada * Corresponding author. Article History: Received 25 March 2021; Accepted 9 March 2022 Byline: Tim J. Boonen [t.j.boonen@uva.nl] (*,a), Wenjun Jiang [wenjun.jiang@ucalgary.ca] (b)

Keywords OR in maritime industry; Berth allocation; Quay crane scheduling; Uncertainty; Review Highlights * A complete review on berth allocation problems under uncertainty is given. * A detailed classification of all papers in the subject is provided. * Methodological approaches to handle uncertainty and their limitations are discussed. * Several promising and important future research directions are identified. Abstract Port terminals play a critical role in the context of world trade since they are the main nodes responsible for connecting sea and land transportation. There are several optimization problems arising in port terminals, and those involving berth allocation are among the most important ones. They constitute the first level of terminal planning operations. As a consequence, the corresponding decisions impact all the subsequent operations in the port terminals. Berth allocation decisions are often integrated with quay crane assignment and/or scheduling decisions. However, the quality of these decisions is greatly affected by unpredictable events that may occur frequently. Since 2006, different approaches have been proposed for solving general berth allocation problems under uncertainty. This paper provides an exhaustive survey of the works published in the literature addressing berth allocation and berth allocation and quay cranes assignment/scheduling problems under uncertainty. The publications are classified into three main classes of approaches: proactive, reactive, and proactive/reactive. An overview of the main methodologies proposed, including stochastic programming, robust optimization, fuzzy programming, and deterministic approaches, is provided. The common sources of uncertainty are identified, and the representation of the uncertain parameters is highlighted. The papers are also classified according to the main objectives to be optimized and the solution methods proposed. We identify several research trends, limitations in the current literature and future research directions. Author Affiliation: (a) ISEG-School of Economics and Management, University of Lisbon, REM - Research in Economics and Mathematics, CEMAPRE, Portugal (b) Department of Mathematics and CIDMA, University of Aveiro, Aveiro, Portugal * Corresponding author. Article History: Received 2 June 2021; Accepted 27 December 2021 Byline: Filipe Rodrigues [frodrigues@iseg.ulisboa.pt] (*,a), Agostinho Agra [aagra@ua.pt] (b)

Keywords Game Theory; Search game; Two-player zero-sum game; Optimal strategies; Discrete time-varying Markov process Abstract We introduce a discrete-time search game, in which two players compete to find an invisible object first. The object moves according to a time-varying Markov chain on finitely many states. The players are active in turns. At each period, the active player chooses a state. If the object is there then he finds the object and wins. Otherwise the object moves and the game enters the next period. We show that this game admits a value, and for any error-term [epsilon]>0, each player has a pure (subgame-perfect) [epsilon]-optimal strategy. Interestingly, a 0-optimal strategy does not always exist. We derive results on the analytic and structural properties of the value and the [epsilon]-optimal strategies. We devote special attention to the important time-homogeneous case, where we show that (subgame-perfect) optimal strategies exist if the Markov chain is irreducible and aperiodic. Author Affiliation: (a) Toulouse School of Economics, Université Toulouse 1 Capitole, France (b) Department of Quantitative Economics, Maastricht University, Netherlands (c) Department of Data Science and Knowledge Engineering, Maastricht University, Netherlands * Corresponding author. Article History: Received 3 December 2020; Accepted 1 March 2022 (footnote)[white star] We would like to thank Steve Alpern, Dietmar Berwanger, Michael Eichler, Rida Laraki, Thomas Lidbetter, Miquel Oliu-Barton, Jérôme Renault, Bernhard von Stengel, Xavier Venel, Yannick Viossat, Bruno Ziliotto, and the audiences of the game theory seminars in Paris and at the London School of Economics for their precious comments and referring us to related literature. We also thank the Associate Editor and three anonymous reviewers for reading the paper very carefully and providing many useful comments that helped us greatly improve the paper. Byline: Benoit Duvocelle [benoit.duvocelle@hotmail.fr] (*,a), János Flesch [j.flesch@maastrichtuniversity.nl] (b), Mathias Staudigl [staudigl@maastrichtuniversity.nl] (c), Dries Vermeulen [d.vermeulen@maastrichtuniversity.nl] (b)

Keywords Finance; Variance swap rates; Self-exciting jumps; Variance risk premium; Variance swap investments Highlights * Studying the information content of variance swap rates on the S&P 500 index. * Proposing a tractable three-factor model for the market index and its variance. * Providing analytical solution to the optimal investment problem in variance swaps. Abstract This paper proposes a tractable three-factor model with self-exciting jumps for the S&P 500 index and its variance. The statistical results show that this new model empirically outperforms the two-factor models widely studied in the literature in terms of fitting variance swap rates on the S&P 500 index across maturities ranging from one month to two years over the sample period from 2008 to 2020. We also provide closed-form solution for variance swap rates and analytically solve the optimal portfolio choice problem in variance swaps for an investor with a power utility function. Unlike the optimal investment with two variance swaps in two-factor models, the investor follows a 'long-short-long' trading strategy involving three swap contracts. Hence, a third swap is not redundant in our three-factor model. In particular, our portfolio optimization exercises illustrate that ignoring a third variance swap in the investment problem may incur significant economic costs in the proposed model. Author Affiliation: (a) Department of Financial and Actuarial Mathematics, School of Science, Xi'an Jiaotong Liverpool University, 215123, China (b) Department of Mathematical Finance, Tianjin University of Finance and Economics, Tianjin, 300222, China * Corresponding author. Article History: Received 30 December 2020; Accepted 4 March 2022 (footnote)[white star] We are very grateful to Emanuele Borgonovo (the Editor) and three anonymous referees for their insightful and constructive comments that substantially improve the paper. We are grateful to Renata Herrerias, the discussant at European Financial Management Association 2018 Annual Meetings, Junye Li, the discussant at 2018 China International Conference in Finance, and Diana Iercosan at 2018 Paris Financial Management Conference for many insightful comments. Xing Jin and Yi Hong gratefully acknowledge the support of the Natural Science Foundation of China [Grant 72071140]. Yi Hong appreciates the financial support from the Young Scholar Programme by Ministry of Education (MoE) (15YJC790026) and Xi'an Jiaotong-Liverpool University (RDF-14-02-51 and KSF-E-31). Byline: Yi Hong [yi.hong@xjtlu.edu.cn] (a), Xing Jin [xingjin2019@outlook.com] (*,b)

Keywords Transportation; Heuristics; Swap-body; Transfers; Mixed integer programming Highlights * We introduce the vessel swap-body routing problem. * We investigate the impact of body transfers on the search space and the solution quality. * We provide an instance set generated based on real-world data. * We introduce a mixed integer programming formulation. * We introduce heuristics for solving the instances. Abstract This paper introduces the Vessel Swap-Body Routing problem (VSBR), a generalization of the pickup and delivery problem with time windows, which considers freight distribution between ports located throughout an inland waterway network. Subject to time windows and precedence constraints, each customer request is associated with a number of containers and must be served via a single body. Bodies are capacitated components that cannot move independently and must therefore be towed by a vessel. Bodies can be transferred between vessels at customer locations or transfer points in order to reduce overall costs. Vessels and bodies can end their routes at any location, meaning they do not need to return to a depot. Moreover, every vessel-body combination is permitted, which greatly expands the size of the solution search space. Although body transfers constitute a fundamental component of this real-world problem, the flexibility such transfers engender poses a huge logistical challenge to the human planners tasked with efficiently scheduling vessel routes. In this paper we model the VSBR as an optimization problem and introduce complementary approaches for solving it. We propose a mixed integer programming formulation and a heuristic approach with tailored neighborhoods for body transfers. To help stimulate further research, a set of instances is introduced based on real-world data and benchmarks are made publicly available. Author Affiliation: (a) KU Leuven, Dept. of Computer Science, Leuven.AI, Leuven B-3000, Belgium (b) Department of Computing, Federal University of Ouro Preto, Brazil * Corresponding author. Article History: Received 25 May 2021; Accepted 4 February 2022 Byline: Vinícius S.M. Gandra [vinicius.gandramartinssantos@kuleuven.be] (*,a,b), Hatice Çalik [hatice.calik@kuleuven.be] (a), Túlio A.M. Toffolo [tulio@toffolo.com.br] (b), Marco Antonio M. Carvalho [mamc@ufop.edu.br] (b), Greet Vanden Berghe [greet.vandenberghe@cs.kuleuven.be] (a)

Keywords Productivity and efficiency; Production functions; Convex non-parametric least squares; Causal models; Deconfounding Highlights * In this paper we consider Convex Nonparametric Least Squares (CNLS) when productivity is introduced. * When productivity shocks are known to the producers, input choices are endogenous and estimators of production function parameters become inconsistent. * As CNLS has excellent properties in terms of approximating arbitrary monotone concave functions, we use it, along with flexible formulations of productivity. * We estimate inefficiency and productivity growth in Chilean manufacturing plants. * Unlike the Cobb-Douglas and translog production functions, the CNLS system is found to admit a causal interpretation. Abstract In this paper we consider Convex Nonparametric Least Squares (CNLS) when productivity is introduced. In modern treatments of production function estimation, the issue has gained great importance as when productivity shocks are known to the producers, input choices are endogenous and estimators of production function parameters become inconsistent. As CNLS has excellent properties in terms of approximating arbitrary monotone concave functions, we use it, along with flexible formulations of productivity, to estimate inefficiency and productivity growth in Chilean manufacturing plants. Inefficiency and productivity dynamics are explored in some detail along with marginal effects of contextual variables on productivity growth, inputs, and output. Additionally, we examine the causal structure between inefficiency and productivity as well as model validity based on a causal deconfounding approach. Unlike the Cobb-Douglas and translog production functions, the CNLS system is found to admit a causal interpretation. Author Affiliation: Montpellier Business School & Lancaster University Management School, LA1 4YX, UK Article History: Received 5 July 2021; Accepted 8 February 2022 Byline: Mike G. Tsionas [m.tsionas@lancaster.ac.uk]

Keywords Productivity and competitiveness; Subsidies; Endogeneity; Semiparametric smooth coefficient models Highlights * A semiparametric smooth coefficient model framework investigates both neutral and non-neutral effects of subsidies. * An original econometric model incorporates the endogeneity of subsidies. * A bias correction identification procedure takes into account the censoring feature of subsidies. Abstract This paper examines the effect of government subsidies on firm-level productivity. The subsidy-promoting policies are oftentimes justified on the ground that subsidies increase the recipient firms' innovation and productivity. We develop a novel (semiparametric) method to structurally identify the firm-level productivity in the presence of subsidies. Unlike previous studies, we assume that subsidies are endogenous. To correct for the endogeneity problem, we use a switching regression in our semiparametric production function. Our method provides an improved framework for estimating the production function with endogenous and/or censored variables. We apply our method to study the effect of subsidies on firm-level productivity in the Chinese machinery industry, using panel data from 1998 to 2007. We find strong empirical evidence that subsidies have a positive effect on firms' persistent productivity. Subsidies may allow firms to invest more on research and development (R&D) and thus improve productivity. Using the available R&D data, we find evidence to support this explanation that more subsidies are associated with higher R&D investment. We also carry out a decomposition analysis to separately examine the subsidy effect on output via the input channel and the persistent productivity channel. Opposite effects are found from the two channels and overall subsidies have a positive effect on a firm's output. Author Affiliation: (a) School of Economics, Huazhong University of Science and Technology, Wuhan, Hubei, China (b) Department of Economics, State University of New York at Binghamton, NY, USA (c) Department of Economics, Oakland University, MI, USA (d) University of Stavanger Business School, Norway * Corresponding author. Article History: Received 26 January 2021; Accepted 13 February 2022 (footnote)[white star] We would like to thank the Editor, Professor Mike Yearworth and three anonymous referees, whose comments substantially improved the paper. We also would like to thank Professors Shunan Zhao, Brian Hardaker, Ivan Korolev, Qiankun Zhou, Zhezhi Hou, and David Slichter for their helpful comments on an earlier version of the paper. Byline: Mingyang Li [mli134@binghamton.edu] (*,a,b), Man Jin [mjin@oakland.edu] (c), Subal C. Kumbhakar [kkar@binghamton.edu] (b,d)

Keywords Multiple objective programming; Branch and bound; Combinatorial optimization; Linear relaxation; Warm-starting Highlights * Develops a branch-and-bound algorithm for multi-objective integer problems. * Uses the linear relaxation as a lower bound set in the algorithm. * Warm-starts the linear relaxation using information from the father node. * Warm-starting the linear relaxation improves efficiency considerably. * Reports extensive computational results. Abstract In this paper we propose a generic branch-and-bound algorithm for solving multi-objective integer linear programming problems. In the recent literature, competitive frameworks has been proposed for bi-objective 0--1 problems, and many of these frameworks rely on the use of the linear relaxation to obtain lower bound sets. When increasing the number of objective functions, however, the polyhedral structure of the linear relaxation becomes more complex, and consequently requires more computational effort to obtain. In this paper we overcome this obstacle by speeding up the computations. To do so, in each branching node we use information available from its father node to warm-start a Bensons-like algorithm. We show that the proposed algorithm significantly reduces the CPU time of the framework on several different problem classes with three, four and five objective functions. Moreover, we point out difficulties that arise when non-binary integer variables are introduced in the models, and test our algorithm on problem that contains non-binary integer variables too. Author Affiliation: Department of Economics and Business Economics, School of Business and Social Sciences, Aarhus University, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark * Corresponding author. Article History: Received 5 August 2021; Accepted 31 January 2022 Byline: Nicolas Forget [nforget@econ.au.dk] (*), Sune Lauth Gadegaard, Lars Relund Nielsen

Keywords Supply chain management; Multi-channel distribution; Manufacturer encroachment; Systematic literature review; Multi-channel supply chain Highlights * Reviews the literature on the manufacturer's perspective of multi-channel distribution systems. * Develops a conceptual framework for analysing the literature. * Investigates determinant factors of the manufacturer for introducing a direct channel. * Classifies network designs according to different design options for distribution systems. * Explores possible strategies that the manufacturer adopts to alleviate conflicts with its retailers. * Investigates operational decision problems in a multi-channel distribution setting. Abstract To reach more customers, many manufacturers utilize multiple distribution channels consisting of a direct and an indirect sales channel. In particular, the strong growth of internet sales (or e-commerce) has driven companies to redesign their distribution channels to take advantage of the opportunities e-commerce offers. Opening a direct sales channel, however, also leads to managerial challenges. The most significant one is channel conflicts that manufacturers encounter when adding a direct channel to an existing traditional channel. Manufacturers that engage in direct selling may compete with their extant independent retailers. Competition between manufacturers and retailers starts when the former intrude into the market (segment) that was traditionally served by the retailers via manufacturer-owned stores and online sales, which is commonly referred to as manufacturer or supplier encroachment. This paper aims to provide a systematic and exhaustive review of multi-channel distribution systems in a combined forward and reverse supply chain where the manufacturer competes with its independently-owned intermediaries (retailers or wholesalers). First, to organize our discussion, all works obtained during the literature search were classified and evaluated in accordance with a proposed conceptual framework. The paper then discusses the sampled works and evaluates possible research gaps. Finally, based on the analysis of the literature, managerial implications and promising future research directions are proposed. Author Affiliation: Institute of Production and Supply Chain Management, Technical University of Darmstadt, Hochschulstr. 1, 64289 Darmstadt, Germany * Corresponding author. Article History: Received 26 April 2021; Accepted 3 December 2021 Byline: Nail Tahirov, Christoph H. Glock [glock@bwl.tu-darmstadt.de] (*)

Keywords Data envelopment analysis; Technical efficiency; Properties; Convex optimization; Second-order cone programming Highlights * Certain well-known slacks-based measures are generalized. * The Hölder means are applied in the generalization process. * The new general measure satisfies many standard properties. * In particular, it satisfies the unique projection property for benchmarking. * The computational implementation of the measure is also shown. Abstract The measurement of technical efficiency is a topic of great interest in microeconomics and engineering. Data Envelopment Analysis (DEA) is one of the existing techniques for measuring technical efficiency. One of the challenges related to DEA is to introduce a 'well-defined' efficiency measure. Overall, it means that the technical efficiency measure should satisfy a list of mathematical and economical properties. Regarding this point, an unresolved question in the DEA literature to date, is whether any measure can satisfy both Indication, also called Pareto-efficiency identification, and uniqueness of the projection point generated by the corresponding efficiency optimization model. With this issue in mind, this paper introduces a new family of measures, inspired on the Range-Adjusted Measure (RAM), which satisfy a list of six properties. This family of measures will be called Generalized Range-Adjusted Measure (GRAM). Additionally, we show in this paper how GRAM can be implemented from a computational point of view and we also provide an economical interpretation of its dual program in terms of (shadow) profit maximization. Finally, an empirical example extracted from the literature serves to illustrate the new methodology. Author Affiliation: Center of Operations Research, University Miguel Hernandez of Elche. Avda. de la Universidad, s/n, Elche 03202 Alicante, Spain * Corresponding author. Article History: Received 16 March 2021; Accepted 2 January 2022 Byline: Juan Aparicio [j.aparicio@umh.es], Juan F. Monge [monge@umh.es] (*)

Keywords Location; Leader's problem; Multipurpose shopping; Consumer choice Highlights * A follower's retail store location problem from the literature is extended. * Best locations for a first and a second entrants are determined. * An exact ad-hoc procedure is adapted to solve small instances. * A new bi-level reactive GRASP procedure finds solutions to larger instances. * The effect of leader's foresight in both the market and the customers is estimated. Abstract This paper extends the follower's retail store location problem of Marianov et al. (2018) to include the leader's decisions. The leader locates its stores knowing that a follower will enter the market later offering a different product. Both maximize their markets given that customers can purchase none, one or two non-essential products on the same trip. The paper determines the best locations for a first and a second entrants through exact and approximated procedures. It turns out that, by locating with foresight, a first entrant can increase the total business in an area for himself and subsequent entrants. We solve the binary programming bi-level resulting problem for small instances by adapting an ad-hoc procedure. Furthermore, a new bi-level reactive GRASP procedure finds solutions for instances of up to 100 nodes in under 3,600 s of CPU time. Author Affiliation: (a) Department of Engineering Sciences, Universidad Andres Bello, Santiago, Chile (b) Department of Electrical Engineering, Pontificia Universidad Católica de Chile and Instituto Sistemas Complejos de Ingeniería (ISCI), Santiago, Chile (c) Faculty of Management, University of New Brunswick, Fredericton, NB, Canada (d) PhD Program in Engineering, Pontificia Universidad Católica de Chile Chile * Corresponding author. Article History: Received 6 May 2021; Accepted 7 January 2022 Byline: Armin Lüer-Villagra [armin.luer@unab.cl] (a,*), Vladimir Marianov (b), H.A. Eiselt (c), Gonzalo Méndez-Vogel (d)

Keywords Problem structuring methods; System dynamics; System perception; Causal Loop Diagrams; Boundary Critique Highlights * Sustainability challenges require coordinated effort from multiple organisations. * Differences in system boundaries are unavoidable in multi-organisational settings. * Ambiguity in system boundaries could reduce the effectiveness of decisions. * This research compares stakeholders' perceptions of system boundaries. * The comparison uses a novel type of thematic analysis of Causal Loop Diagrams. Abstract Differences in system boundaries and problem framings are unavoidable in multi-organisational decision-making. Unstructured problems, such as the grand challenges, are characterised by the existence of multiple actors with different perspectives and conflicting interests, and they require a coordinated effort from multiple organisations. Within this context, this paper aims to understand stakeholders' perceptions of system boundaries and problem framings, and their potential effects on decision-making by systematically comparing different stakeholder groups' causal maps around the same shared concern. Bridging notions from Operational Research, System Dynamics and Organisational Studies, the comparison is based on a novel type of thematic analysis of Causal Loop Diagrams (CLDs) built with each stakeholder group on their perceptions of a given system. The proposed integrated approach combines qualitative with quantitative analysis, such as the centrality of the variables and the structure of the CLDs. Such CLDs comparison provides an intuitive way to visualise differences and similarities of the thematic clusters of variables, underlining factors influencing the shared concern. This could be considered a starting point for more shared understanding as well as more integrated holistic perceptions of the system and, consequently, a more systemic decision-making. Furthermore, for the sake of replicability, this paper also presents a qualitative participatory System Dynamics modelling process aimed to define the key aspects of a problem for each group of stakeholders to support a collaborative multi-organisational decision-making process. The research is based on the activities carried out for an urban regeneration case study in Thamesmead, London, United Kingdom. Author Affiliation: Institute for Environmental Design and Engineering, The Bartlett Faculty of The Built Environment, University College London, UK * Corresponding author. Article History: Received 31 December 2020; Accepted 19 December 2021 Byline: Irene Pluchinotta [i.pluchinotta@ucl.ac.uk] (*), Giuseppe Salvia, Nici Zimmermann

Keywords Transportation; Hazardous material transportation; Routing; Routing-scheduling; Network design; Comprehensive review Highlights * Providing a comprehensive but microscopic review on hazmat transportation problems. * Classifying the papers from an OR viewpoint. * Providing a detailed discussion on the role of transportation modes in hazmat transportation problems. Abstract This paper provides a comprehensive review in the domain of hazardous material transportation from an Operational Research point of view. The paper's focus lies on hazmat routing, routing-scheduling, and network design problems. The objective of this review paper is twofold: (1) reviewing the models' assumptions, objectives and constraints, decisions, input parameters, basic modeling/solution techniques, and case studies, and (2) highlighting the underlying features and challenges in designing the models with different transportation modes. Besides, the most significant research gaps in the literature are identified through a systematic in-depth review at a micro-level. Finally, a set of promising future research directions is proposed upon from the authorities could draw better decisions. As a key finding after performing this review, we believe that a considerable number of promising future research directions consist in hybridizing different problems, i.e., amount to borrowing some key properties from a problem and integrating them into another problem. This has led to valuable research studies in the literature of hazmat transportation problems. Author Affiliation: (a) Department of Infrastructure Engineering, University of Melbourne, Melbourne, VIC, Australia (b) Lab-STICC, UBL, IMT Atlantique, Brest F-29238, France (c) CIRRELT and Département de mathématiques et génie industriel, Polytechnique Montréal, P.O. Box 6079, Station Centre-Ville, Montréal H3C 3A7, Canada (d) Centre of Excellence in Supply Chain and Transportation (CESIT), KEDGE Business School, Bordeaux, France (e) Department of Transportation Engineering, Isfahan University of Technology, Isfahan, Iran * Corresponding author. Article History: Received 9 February 2021; Accepted 24 November 2021 Byline: Seyed Sina Mohri (a), Mehrdad Mohammadi [mehrdad.mohammadi@imt-atlantique.fr] (b,*), Michel Gendreau (c), Amir Pirayesh (d), Ali Ghasemaghaei (e), Vahid Salehi (e)

Keywords combinatorial optimization; Assembly line balancing; Multi-manned workstations; Dependent task times, Ad-hoc heuristic; Relax-and-Fix Highlights * A MALBP-1 variant with dependent task times is studied * A heuristic that solves a partition problem with constraints is presented * HEUR_PART gets better results than any other procedure published for this variant * An improved mathematical model is proposed Abstract This paper aims to study a variant of the multi-manned assembly line balancing problem (MALBP), which considers the possibility of multiple workers simultaneously performing different tasks at the same workstation. In most cases it is assumed that task times are deterministic. This paper takes into account possible interferences between workers and deals with the MALBP with task times depending on the number of workers at the station. Different procedures are developed: resolutions on the basis of a mathematical model, two Relax-and-Fix procedures, a heuristic based on solving a partition problem with constraints (named 'HEUR_PART') and a set of other variants of the HEUR_PART procedure. The computational experiments indicate that HEUR_PART and the HEUR_PART_SGL variant are the proposals that perform best. Additionally, we show that they obtain better results than the ones published in the literature. Author Affiliation: Institute of Industrial and Control Engineering (IOC), Universitat Politècnica de Catalunya (UPC), Av. Diagonal 647 (Building ETSEIB), 11th floor, Barcelona 08028, Spain * Corresponding author. Article History: Received 12 January 2021; Accepted 1 December 2021 Byline: Enric Andreu-Casas, Alberto García-Villoria [alberto.garcia-villoria@upc.edu] (*), Rafael Pastor [rafael.pastor@upc.edu]

Keywords Game theory; RFID; Inventory inaccuracy; Supply chain management Highlights * This paper examines RFID strategies under horizontal and vertical competition. * The powerful supplier has the incentive and is more inclined to adopt RFID than the follower. * When competition increases, the suppliers are more likely to forgo using RFID. * The equilibrium RFID adoption strategy can bring all members to the Pareto outcome. Abstract Radio frequency identification (RFID) technology has proved to be an effective way to eliminate inventory inaccuracy, which is very prevalent in many industries. Inspired by the case of Wal-Mart facing difficulties when it required its suppliers to adopt RFID, this paper investigates RFID adoption strategies in a decentralized supply chain with two competing suppliers and a dominant retailer facing inventory inaccuracies. The two suppliers first sequentially determine whether to adopt RFID. Then, the supply chain members sequentially set their pricing policies under the wholesale price contract. We characterize the optimal wholesale prices, retail prices, and profits under different RFID adoption strategies and further examine the equilibrium results of RFID adoption. Our findings reveal that when only the powerful supplier uses RFID, the follower's profit first increases and then decreases as the inventory availability rate increases; however, when only the follower supplier adopts RFID, the profit of the powerful supplier that forgoes RFID increases as the inventory availability rate increases. Importantly, inventory inaccuracies and tag costs have substantial effects on the equilibrium RFID adoption strategy under upstream competition. The powerful supplier has the incentive and is more inclined to adopt RFID than the follower. Under intense upstream competition, suppliers are more likely to forgo the use of RFID. The equilibrium RFID adoption strategy can bring all supply chain members to a Pareto optimal outcome when both inventory availability rates are low or one is close to 1 while the other is low. Author Affiliation: Department of Management Science and Engineering, School of Business, East China University of Science and Technology, 200237, Shanghai, China * Corresponding author at: 130 Meilong Road, Xuhui District, Shanghai 200237, China. Article History: Received 21 January 2021; Accepted 3 December 2021 Byline: Feng Tao, Liang Wang, Tijun Fan [tjfan@ecust.edu.cn] (*), Hao Yu

Keywords Assignment; Dormitories; Stable matching; Many-to-many matching; Incentive compatibility Highlights * Socio-economic and academic achievements considerations in the assignment process of student-groups to dormitories. * Stable assignment under common preference-lists of dormitories over the student-groups. * Polynomial time algorithm for assigning student-groups to dormitories. * Polynomial time algorithm for listing all the stable assignments. * Incentive compatibility issues in student-groups assignment. Abstract This paper generalizes results of former papers on the assignment of students to dormitories, under an entrance criterion, by allowing students to apply in groups. A group-application means that its applicants ask to be assigned to the same dormitory, and otherwise they prefer living off-campus. The underlying assumption in our model is that the dormitories share a common preference over the student-groups, which is given by a strictly increasing ranking of their credit scores. The definition of a quasi-stable outcome is adjusted in order to incorporate student-group applications, and we prove that such an outcome always exists. Furthermore, a polynomial-time algorithm that finds all the quasi-stable outcomes is proposed. Apparently, not all properties of the single students' model continue to hold under group-applications. Finally, we consider the incentive compatibility property of the proposed algorithm, and describe a specific quasi-stable outcome for which no subset of student-groups can gain by misrepresenting their preferences over the dormitories. Author Affiliation: Coller School of Management, Tel Aviv University, Tel Aviv 69978, Israel * Corresponding author. Article History: Received 18 February 2020; Accepted 30 December 2021 Byline: Nitsan Perach [nitsan.perah@gmail.com] (*), Shoshana Anily [anily@tauex.tau.ac.il]

Keywords Dynamic programming; Target benefit pension plan; Cobb-Douglas utility; Optimal investment; Stochastic differential utility Highlights * This paper proposes an investment and benefit adjustment problem for a target benefit pension plan. * The pension plan provides sustainable benefits with intergenerational risk sharing. * The objective is to maximize the weighted product of benefit and wealth via Cobb-Douglas utility. * Epstein-Zin recursive utility is considered as an extension. * Optimal strategies are derived explicitly and verification theorem is proved. Abstract This paper studies an optimal investment and benefit adjustment problem for a target benefit pension plan. The pension sponsor can adjust the benefit level to guarantee the stable operation of the plan. The pension is allowed to invest in a risk-free bond and a stock. The weighted product of the benefit outgo and pension wealth is considered in the objective function, which is taken in the form of Cobb-Douglas utility. Thus the plan takes both the benefit level and terminal wealth of the pension into account and then the benefit payment are dependent on the financial situation of the plan. By applying dynamic programming approach, we establish the corresponding Hamilton-Jacobi-Bellman equation and derive the optimal investment-benefit strategy and the value function explicitly. The verification theorem is presented and proved. Furthermore, the recursive utility is considered as an extension and we find that the elasticity of intertemporal substitution has a positive effect on the optimal benefit level. Finally, numerical examples are given and demonstrate that this pension scheme is sustainable and can provide stable and consecutive incremental benefit payment for future generations. Author Affiliation: (a) School of Mathematics, Tianjin University, Tianjin 300072, P.R. China (b) School of Finance, Tianjin University of Finance and Economics, Tianjin 300222, P.R. China * Corresponding author. Article History: Received 26 September 2020; Accepted 18 November 2021 Byline: Hui Zhao [zhaohuimath@tju.edu.cn] (a), Suxin Wang [wangsuxin@tjufe.edu.cn] (*,b)

Keywords Supply chain management; Environmental green reputation; Wholesale-price contract; Revenue-sharing contract; Myopic retailer Highlights * We consider a supply chain with environmentally concerned consumers. * We assess the impact of environmental performance on strategies and outcomes. * We compare revenue-sharing and wholesale-pricing contracts. * We analyze the impact of retailer's myopia on equilibrium strategies and outcomes. Abstract Consumers are increasingly concerned about pollution and are, at least in part, making their purchases accordingly. In this paper, we consider a supply chain where demand depends on the manufacturer's environmental reputation, an asset that can only be built over time. We assume that this reputation depends on information emanating from the manufacturer itself about its environmental actions and on its objective environmental record when compared to an industry standard. In this paper, we look at the impact of consumers' environmental concern on the strategies and outcomes of a supply chain. As the retailer has a direct influence on sales through its pricing policy, it seem more realistic to take a supply chain perspective instead of a single-firm one. Therefore, the contractual arrangement in the supply chain becomes a relevant issue. We model the supply chain as a two-player dynamic game and characterize and compare the equilibrium strategies and outcomes under wholesale-price and revenue-sharing contracts. We analyze the impact of the sharing parameter, the industry pollution standard and consumers' degree of environmental sensitivity on the results, and in particular, on the region in the parameter space where a revenue-sharing contract is Pareto improving with respect to a wholesale-price contract. Also, we examine whether it is in the best interest of the retailer to behave myopically when setting its price. Author Affiliation: (a) School of Business, Qingdao University, Qingdao 266071, China (b) Saint Petersburg State University, Saint Petersburg, Russia (c) Institute of Applied Mathematics of Shandong, Qingdao 266071, China (d) School of Mathematics and Statistics, Qingdao University, Qingdao 266071, China (e) Chair in Game Theory and Management, GERAD, HEC, Montreal, Canada (f) School of Mathematics and Statistics, Qingdao University, Qingdao 266071, China * Corresponding author. Article History: Received 20 July 2021; Accepted 19 November 2021 (footnote)[white star] We would like to thank three anonymous Reviewers for their helpful comments. The work of the second author was supported by the Shandong Province 'Double-Hundred Talent Plan' (No. WST2017009). The work of the third author was supported by Grant RGPIN-2021-02462, NSERC, Canada. The work of the fourth author was supported by National Natural Science Foundation of China(No. 71571108). Byline: Fanjun Yao [yaofanjun@126.com] (a), Elena Parilina [e.parilina@spbu.ru] (b,c,d), Georges Zaccour [georges.zaccour@gerad.ca] (*,e), Hongwei Gao [gaohongwei@qdu.edu.cn] (f)

Keywords Production; Assembly line balancing; Optimization; Survey Highlights * We survey the assembly line balancing research of the past 15 years. * Progress in all stages of the decision-making process is elaborated. * Important new problems, models, and algorithms are surveyed. * Future research needs are identified. Abstract Ever since the times of Henry Ford up to today's industry 4.0 era, flow-oriented assembly processes, where an assembly line conveys the workpieces from workstation to workstation, are very important for mass-producers in manifold branches of industry. Among the most elementary optimization problems in this context is the assembly line balancing problem, which decides on the division of labor among the stations of an assembly line. This paper surveys the scientific literature on assembly line balancing that has been published since the last major review papers have appeared in 2006 and 2007, respectively. We cover all essential stages of the decision making process: we address novel methods to efficiently gather the relevant (precedence graph) data, review especially new problem variants and models treated in the literature, and survey the most important algorithmic developments. Furthermore, we outline a possible research agenda for the next fifteen years. Author Affiliation: (a) Lehrstuhl für Operations Management, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, Jena 07743, Germany (b) Lehrstuhl für Management Science, Friedrich-Schiller-Universität Jena, Carl-Zeiß-Straße 3, Jena 07743, Germany * Corresponding author. Article History: Received 20 August 2021; Accepted 22 November 2021 Byline: Nils Boysen [https://www.om.uni-jena.de] (*,a), Philipp Schulze [philipp.schulze@uni-jena.de] (b), Armin Scholl [https://www.mansci.uni-jena.de] (b)

Keywords Multi-agent systems; Random walks; Aerial surveillance; Synchronization Highlights * A team of UAVs to efficiently patrol a terrain is considered. * Each robot flies around an assigned area and periodically shares information with the neighbors. * In case of fail, a remaining robot pass to the neighboring area to ensure robustness of the system. * Random strategies are studied both theoretically and experimentally. * Simulations show that theoretical results are in good agreement with the experiments. Abstract A group of cooperative aerial robots can be deployed to efficiently patrol a terrain, in which each robot flies around an assigned area and shares information with the neighbors periodically in order to protect or supervise it. To ensure robustness, previous works on these synchronized systems propose sending a robot to the neighboring area in case it detects a failure. In order to deal with unpredictability and to improve on the efficiency in the deterministic patrolling scheme, this paper proposes random strategies to cover the areas distributed among the agents. First, a theoretical study of the stochastic process is addressed in this paper for two metrics: the idle time, the expected time between two consecutive observations of any point of the terrain and the isolation time, the expected time that a robot is without communication with any other robot. After that, the random strategies are experimentally compared with the deterministic strategy adding another metric: the broadcast time, the expected time elapsed from the moment a robot emits a message until it is received by all the other robots of the team. The simulations show that theoretical results are in good agreement with the simulations and the random strategies outperform the behavior obtained with the deterministic protocol proposed in the literature. Author Affiliation: (a) Departamento de Matemática Aplicada II, Universidad de Sevilla, Spain (b) Departamento de Matemáticas, CINVESTAV, Mexico City, Mexico * Corresponding author. Article History: Received 29 July 2020; Accepted 26 November 2021 (footnote)1 Supported by Spanish Government under the grant agreement FPU14/04705. He is partially supported by project GALGO (Spanish Ministry of Economy and Competitiveness, MTM2016-76272-R AEI/FEDER,UE). (footnote)2 Partially supported by project GALGO (Spanish Ministry of Economy and Competitiveness, MTM2016-76272-R AEI/FEDER,UE) Byline: Luis E. Caraballo [lcaraballo@us.es] (1,a), José M. Díaz-Báñez [dbanez@us.es] (*,2,a), Ruy Fabila-Monroy [ruyfabila@math.cinvestav.edu.mx] (b), Carlos Hidalgo-Toscano [cmhidalgo@math.cinvestav.mx] (b)

Keywords Integer programming; Robust optimization; Branch-and-price; Parallel machine scheduling Highlights * A robust reformulation of a machine scheduling problem that minimizes the worst-case total tardiness for unrelated parallel machines with sequence-dependent setups and uncertain processing times has been proposed. * An efficient solution methodology that utilizes a branch-and-price algorithm that exploits the particular properties of the problem has been developed. * The importance of Pareto efficiency has been shown, and extensions of the related solution methodology are presented. * Monte Carlo simulation results have shown that the robust approach's improvement can get as high as 56% compared with the deterministic approach. Abstract This paper studies a machine scheduling problem that minimizes the worst-case total tardiness for unrelated parallel machines with sequence-dependent setup and uncertain processing times. We propose a robust optimization reformulation of the related machine scheduling problem and discuss several important properties of the mathematical model and the reformulation approach. The proposed model generalizes robust parallel machine scheduling problems by including sequence-dependent setup times and ellipsoidal uncertainty sets. Another key contribution of the paper is to show that scheduling problems usually have alternative optimal solutions for the worst-case tardiness objective, whose performance under nominal processing times may vary or vice a versa. This issue has been addressed by studying the Pareto efficient extensions of the proposed robust optimization models to provide solutions that are immune to changes in processing times. A branch-and-price algorithm has been developed to solve realistically sized instances in less than one hour, which a commercial solver cannot achieve. Numerical results show the effectiveness of the proposed approach since realistically sized instances such as (4 machines, 32 jobs) and (150 machines, 300 jobs) can be solved to optimality within the time limit, and the (average) objective function value improvement made by the robust approach can get as high as 56% compared with the (nominal) optimal solutions that ignore uncertainty in problem data. Author Affiliation: (a) Özyegin University, Istanbul, Turkey (b) Istanbul Bilgi University, Istanbul, Turkey * Corresponding author. Article History: Received 3 May 2021; Accepted 12 November 2021 Byline: Ihsan Yanikoglu (*,a), Tonguc Yavuz (a,b)

Keywords Packing; 2D bin packing; Guillotine; Heuristic; Variable-sized bins Highlights * Heuristic for solving the 2D bin packing problem with guillotine constraints. * Supports variants with variable-sized bins and 90-degree rotation of items. * Combines the ruin and recreate paradigm with a goal-driven approach. * Experiments demonstrate the effectiveness of the introduced heuristic. Abstract This paper addresses the two-dimensional bin packing problem with guillotine constraints. The problem requires a set of rectangular items to be cut from larger rectangles, known as bins, while only making use of edge-to-edge (guillotine) cuts. The goal is to minimize the total bin area needed to cut all required items. This paper also addresses variants of the problem which permit 90.sup.[ring operator] rotation of items and/or a heterogeneous set of bins. A novel heuristic is introduced which is based on the ruin and recreate paradigm combined with a goal-driven approach. When applying the proposed heuristic to benchmark instances from the literature, it outperforms the current state-of-the-art algorithms in terms of solution quality for all variants of the problem considered. Author Affiliation: KU Leuven, Department of Computer Science, NUMA, Belgium * Corresponding author. Article History: Received 13 January 2021; Accepted 17 November 2021 Byline: Jeroen Gardeyn [jeroen.gardeyn@kuleuven.be] (*), Tony Wauters [tony.wauters@kuleuven.be]

Keywords Routing; Electric vehicles; Recharging; Battery swapping; Scheduling and synchronisation Highlights * An EVRPTW with RSs and synchronised mobile battery swapping is proposed. * An exact and a heuristic solution method are developed. * Comparative analyses of different logistics scenarios by ECVs are performed. * Cost and emissions savings and ECVs extra-urban delivery opportunities are reported. Abstract A primary challenge in goods distribution using Electric Commercial Vehicles (ECVs) pertains to tackling their limited driving range. This paper proposes a multi-faceted approach towards increasing the driving range of ECVs by coordinating the options of: (i) intra-route recharging at an intermediate Recharging Station (RS), with (ii) synchronised en-route battery swapping services performed by Battery Swapping Vans (BSVs) at a pre-planned rendezvous time and space. We introduce and solve a variant corresponding to an Electric Vehicle Routing Problem with Time Windows, RSs and Synchronised Mobile Battery Swapping (EVRPTW-RS-SMBS). In the proposed model, route planning is carried out synchronously for two interdependent fleets, i.e., ECVs and BSVs, which work in tandem to complete the delivery tasks. To address methodological complications arising from the simultaneous consideration of intra-route recharging at RSs and the synchronised battery swapping on-the-fly, the paper develops a pre-optimisation procedure based on a Non-Dominated Path Identification (NDPI) algorithm that is used in deriving a significantly strengthened path-based formulation of the problem, and an efficient dynamic programming based heuristic algorithm. To gain practical insights on the economic and environmental added value and viability of the proposed logistics model, we compare different scenarios for goods distribution using ECVs in urban and regional levels in London and Southeast England, respectively. A set of numerical experiments are further performed to demonstrate the efficiency of the proposed algorithms. Our results indicate significant cost and emissions savings and an opportunity for going beyond last mile local deliveries using ECVs with the proposed logistics model. Author Affiliation: (a) Centre for Logistics and Heuristic Optimisation (CLHO), Kent Business School, University of Kent, Chatham ME4 4TE, UK (b) Centre for Transport and Logistics (CENTRAL), Department of Management Science, Lancaster University Management School, Lancaster LA1 4YX, UK * Corresponding author. Article History: Received 17 December 2020; Revised 22 September 2021; Accepted 25 September 2021 Byline: Ramin Raeesi [r.raeesi@kent.ac.uk] (a,*), Konstantinos G. Zografos [k.zografos@lancaster.ac.uk] (b)

Keywords OR in societal problem analysis; Ecosystems; Innovation-driven entrepreneurship; Review; Applications of OR Highlights * The application of OR to Entrepreneurial Ecosystems (EEs) is fragmented. * We present a problem-oriented typology of limitations of EE research. * These problems connect the OR community to the domain area. * We review OR approaches that address the four identified problems. * We synthesize critical issues and present an agenda for future research. Abstract Innovation-driven entrepreneurship has become a focus for economic development and received increasing attention from policy makers and academics over the last decades. While consensus has been reached that context matters for innovation and entrepreneurship, little evidence and decision support exists for policy makers to effectively shape the environment for growth-oriented companies. We present the entrepreneurial ecosystem concept as a complex systems-based approach to the study of innovation-driven entrepreneurial economies. The concept, in combination with novel data sources, offers new opportunities for research and policy, but also comes with new challenges. The aim of this paper is to take stock of the literature and build bridges for more transdisciplinary research. First, we review emergent trends in ecosystem research and provide a typology of four overarching problems based on current limitations. These problems connect operational research scholars to the context and represent focal points for their contributions. Second, we review the operational research literature and provide an overview of how these problems have been addressed and outline opportunities for future research, both for the specific problems as well as cross-cutting themes. Operational research has been invaluable in supporting decision-makers facing complex problems in several fields. This paper provides a conceptual and methodological agenda to increase its contribution to the study and governance of entrepreneurial ecosystems. Author Affiliation: (a) GW School of Business, George Washington University, Funger Hall, 2201 G Street NW, Washington, D.C. 20052, USA (b) School of Production Engineering and Management, Technical University of Crete, University Campus, 73100 Chania, Greece (c) Hunter Centre for Entrepreneurship, University of Strathclyde, 199 Cathedral Street, Glasgow, G4 0QU, UK * Corresponding author. Article History: Received 7 September 2020; Accepted 13 October 2021 Byline: Elias G. Carayannis [caraye@gwu.edu] (a), Evangelos Grigoroudis [vangelis@ergasya.tuc.gr] (b,*), Bernd Wurth [bernd.wurth@strath.ac.uk] (c)

Keywords Humanitarian coverage path planning; Unmanned aerial vehicle routing; Greedy randomized adaptive search procedure Highlights * A novel approach for humanitarian coverage path planning using UAVs. * The cumulative UAV routing problem formulation. * Three effective multithreaded GRASP-VND metaheuristic implementations. * Obtained best known solutions for the cumulative capacitated vehicle routing problem. Abstract This paper presents a Cumulative Unmanned Aerial Vehicle Routing Problem (CUAVRP) approach to optimize Humanitarian Coverage Path Planning (HCPP). Coverage path planning consists of finding the route which covers every point of a certain area of interest. This paper considers a Search & Rescue mission, using a homogeneous fleet of Unmanned Aerial Vehicles (UAVs). In this scenario, the objective is to minimize the sum of arrival times at all points of the area of interest, thus, completing the search with minimum latency. The HCPP problem is transformed into a Vehicle Routing Problem by using an approximate cellular decomposition technique to discretize the area into a grid, where the rectangles represent the UAV sensor's field of view. The center points of the formed rectangles, become the nodes used for a UAV routing problem. This approach uses the objective of minimizing the sum of arrival times at customers, found in the Cumulative Capacitated Vehicle Routing Problem (CCVRP), adjusted for the Search & Rescue Coverage Path Planning using UAVs. The Min-max objective is also implemented and tested. Three versions of a Parallel Weighted Greedy Randomized Adaptive Search Procedure - Variable Neighborhood Decent (GRASP-VND) algorithm is implemented to solve the Cumulative UAV Routing Problem for Humanitarian Coverage Path Planning. Author Affiliation: Technical University of Crete, School of Production Engineering and Management, University Campus, Chania 73100, Greece * Corresponding author. Article History: Received 2 November 2020; Accepted 7 September 2021 Byline: Nikolaos A. Kyriakakis [nkyriakakis@isc.tuc.gr], Magdalene Marinaki [magda@dssl.tuc.gr], Nikolaos Matsatsinis [nikos@ergasya.tuc.gr], Yannis Marinakis [marinakis@ergasya.tuc.gr] (*)

Keywords Combinatorial optimization; Flow shop scheduling; Early and late work; Dynamic programming; FPTAS Highlights * Two-machine ow shop scheduling to maximize total early work is considered. * A dynamic programming approach running in O(n.sup.2d.sup.2) time is proposed. * A fully polynomial time approximation scheme (FPTAS) is developed. * The approximation results work for the weighted model - if a specific constraint is satisfied. Abstract This paper considers scheduling in a two-machine flow shop to maximize the total early work subject to a common due date. The early work of a job is a parameter defined as the total amount of the job that is processed before the specified due date. We mainly focus on the unweighted model in this paper, and propose a dynamic programming approach running in O(n.sup.2d.sup.2) time (compared with the previous result in O(n.sup.2d.sup.4) time for the weighted case discussed in the literature). Then we analyse the problem from an approximation point of view, in which we first show that Johnson's algorithm, one of the most classical ones in flow shop scheduling, can only achieve the worst performance ratio for the considered problem (although it is an optimal one for makespan minimization). With the motivation of proposing better approximation algorithms, we further design a fully polynomial time approximation scheme (FPTAS). Finally, we point out that the approximation results also work for the weighted model - if a specific constraint is satisfied. Author Affiliation: (a) Liaoning University of Technology, School of Electronics and Information Engineering, Shiying 169, Jinzhou 121001, China (b) Dalian University of Technology, School of Software, Tuqiang 321, Dalian 116023, China (c) National Yang Ming Chiao Tung University, Institute of Information Management, Shinchu 300, Taiwan (d) Poznan University of Technology, Institute of Computing Science, Piotrowo 2, Poznan 60-965, Poland (e) European Centre for Bioinformatics and Genomics, Polish Academy of Sciences, Piotrowo 2, Poznan 60-965, Poland * Corresponding author. Article History: Received 21 February 2021; Accepted 30 July 2021 Byline: Xin Chen (a), Qian Miao (b), Bertrand M.T. Lin [bmtlin@mail.nctu.edu.tw] (*,c), Malgorzata Sterna (d), Jacek Blazewicz (d,e)

Keywords Project management; Real option; Variance risk premium; Expansion option; Abandonment option Highlights * Variance risk premium (VRP) raises value of real options to expand and to abandon. * Option to abandon is more sensitive to VRP than the option to expand. * Abandonment add-on moderates VRP delay effect more than a re-expansion add-on. * VRP delays both abandoning and expanding the projects. * In evaluation of projects, it is crucial to include both follow-up add-ons and VRP. Abstract This paper focuses on the variance risk premium of project returns and its impacts on the real options to expand and to abandon a project. Variance risk premium measures the hedging costs associated with the time-varying variance of the returns. We find that the variance risk premium increases the real option value to expand and to abandon a project. Hence, the variance premium delays both abandoning and expanding the project. Our setting also enables us to study the multi-stage decisions with real options under the variance risk premium. For example, we consider an abandonment or a re-expansion add-on attached to an expansion project, which is a reminiscence of how our framework facilitates modeling compound real option structures in the presence of the variance risk premium. We present two applications of our models that involve Ford Motor company and battery storage investments for electricity distribution networks. These cases demonstrate how the proposed framework in this paper can be applied to real world decisions, and, moreover, they establish a baseline for how much decisions can be improved when variance risk premium is included in the modeling. Author Affiliation: (a) College of Business Administration, California State University, San Marcos, 333 S. Twin Oaks Valley Road, San Marcos CA 92096, USA (b) Carmona College of Business, Saginaw Valley State University, Saginaw, MI, USA * Corresponding author. Article History: Received 9 September 2019; Accepted 12 October 2021 (footnote)1 Data and codes to reproduce the paper's results are provided at http://www.babakl.com/research. Byline: Hedayat Alibeiki [halibeiki@csusm.edu] (*,a), Babak Lotfaliei [blotfali@svsu.edu] (1,b)

Keywords Routing; Pickup and delivery problems; Ring; Computational complexity Highlights * A new class of Pickup and Delivery problems on circular routes (rings) is introduced. * A classification scheme is proposed. * Complexity proofs are given for variants with single direction of travel on the ring. * Polynomial algorithms and ILP models are proposed. * Computational experiments demonstrate the efficiency of the mathematical formulations. Abstract In this paper we introduce a new class of Pickup and Delivery problems on circles (or rings). These problems arise in the field of public transportation systems where autonomous (i.e. driverless) vehicles travel on circular networks. We consider a set of stations arranged in a circle and a set of transportation requests. Each request asks for the transportation of a certain quantity from a pickup station to a delivery station. A fleet of capacitated vehicles is available at the depot. In the first part of the paper we propose a classification scheme for these problems. In the second part, we address the variants in which the vehicles are allowed to move in a single direction of the circle (either clockwise or counterclockwise) and the objective is to minimize the number of tours on the ring while serving all the requests. We provide a complexity analysis for this class of problems. We develop polynomial time algorithms for the variants that are polynomially solvable and proofs of NP-hardness for the variants that are NP-hard. In addition, for the latter, we provide mathematical formulations and perform computational tests that show the effectiveness of these formulations. Finally, we compare optimal solutions with those obtained using a straightforward greedy algorithm. Author Affiliation: (a) Université Clermont Auvergne, CNRS, UMR 6158 LIMOS, F-13541 Gardanne France (b) ESSEC Business School, 3 Avenue Bernard Hirsch, 95000 Cergy, France (c) Mines Saint-Etienne, Univ. Clermont Auvergne, CNRS, UMR 6158 LIMOS, Centre CMP, F-13541 Gardanne France (d) LIMOS, Institut Supérieur d'Informatique de Modélisation et leurs Applications and ISIMA, Campus des Cézeaux, Aubiére Cedex, France * Corresponding author. Article History: Received 23 January 2021; Accepted 28 July 2021 (footnote)1 This work was sponsored by a public grant overseen by the French National Research Agency as part of the 'Investissements d'Avenir' through the IMobS3 Laboratory of Excellence (ANR-10-LABX-0016) and the IDEX-ISITE initiative CAP 20--25 (ANR-16-IDEX-0001). Byline: Manuel Trotta [manuel.trotta@emse.fr] (*,1,a), Claudia Archetti [archetti@essec.edu] (b), Dominique Feillet [dominique.feillet@mines-stetienne.fr] (c), Alain Quilliot [alain.quilliot@isima.fr] (d)

Keywords Inventory; Supply chain management; Omnichannel; Discounts; Critical level; Lost-sales Highlights * We consider a typical omnichannel retail network. * We study a two-echelon critical level inventory model with discounts and lost sales. * We propose an efficient approximation method of the average costs. * We show via extensive numerical experiments that the approximation performs well. * We discuss the cases where the proposed policy is beneficial. Abstract In this paper, we study an inventory model for an omnichannel retailer, that is, a retailer that sells items both via brick-and-mortar stores and online. Online items are delivered from a warehouse, which also replenishes the stores. When the inventory in a store drops below a certain level, the retailer offers customers a discount for purchasing online. In this way, the retailer can save items for customers who need the item immediately and thus avoid lost sales. For this model, we propose an approximation method for calculating the average inventory costs for one store and one warehouse and an optimization procedure for the case of more stores. Using extensive numerical experiments, we show that the approximations are very close to the performance measured via simulation. Finally, we show that by adopting the discounts policy proposed in this paper, the retailer can reduce its total cost, on average, by 8.5% compared to the no-discounts policy. Author Affiliation: (a) Department of Applied Mathematics, Khalifa University, Abu Dhabi, United Arab Emirates (b) Stochastic Operations Research, Department of Applied Mathematics, University of Twente, the Netherlands (c) Department of Industrial and System Engineering, Khalifa University, Abu Dhabi, United Arab Emirates (d) Research Center on Digital Supply Chain and Operations Management, Khalifa University, Abu Dhabi, United Arab Emirates * Corresponding author at: Department of Applied Mathematics, Khalifa University, Abu Dhabi, United Arab Emirates. Article History: Received 3 August 2020; Accepted 6 July 2021 Byline: Adriana F. Gabor [adriana.gabor@ku.ac.ae] (*,a,d), Jan-Kees van Ommeren [j.c.w.vanommeren@utwente.nl] (b), Andrei Sleptchenko [andrei.slecptchenko@ku.ac.ae] (c,d)

Keywords Routing; Three-dimensional loading; Split delivery; Column generation Highlights * We study the split heterogeneous vehicle routing problem with loading constraints. * A column generation-based heuristic algorithm is proposed. * Straightforward loading patterns are produced using a heuristic algorithm. * The proposed algorithm requires less running time than literature algorithms. * Experiments are performed on benchmark and large real-world instances. Abstract This paper introduces a complex real-world problem on a large scale that combines the split delivery heterogeneous vehicle routing problem with three-dimensional loading and considers new routing and loading constraints. The problem aims to find a set of routes with minimum transportation cost by satisfying the demand of all customers and loading constraints. We propose a column generation-based heuristic algorithm that employs three heuristic algorithms to solve the subproblem and a hybrid algorithm for loading. Computational experiments on the literature instances indicate that the proposed algorithm can produce very near solutions to the literature algorithm's solutions in significantly shorter running times. This paper introduces real-world instances with 230 to 850 customers, several times larger than the existing benchmarks. The results of the proposed algorithm for real-world instances are effective, and compared to the current situation, it leads to a reduction of 20% in the average total cost of transportation. Also, the average number of vehicles is reduced by 36%. Author Affiliation: Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran * Corresponding author. Article History: Received 20 August 2020; Accepted 14 August 2021 Byline: Maryam Rajaei, Ghasem Moslehi [moslehi@iut.ac.ir] (*), Mohammad Reisi-Nafchi

Keywords Risk management; Peer-to-peer insurance; InsurTech; Decentralization; Credibility theory Highlights * First paper to exploit peer-to-peer insurance and mutual aid in an analytical framework. * New applications of optimization methods. * Unifying framework of network structure. * Theoretical justification of market observation on cost reduction and stability. Abstract Peer-to-peer (P2P) insurance is a decentralized network in which participants pool their resources together to compensate those who suffer losses. The rise of P2P insurance in Western countries, such as Friendsurance and Lemonade, has been viewed as a disruption to the traditional insurance industry in the same way Uber is to the taxi industry. A similar business model of mutual aid, such as the model developed by Xianghubao, has become popular in the East. It is a model designed to provide financial support to those in need and to distribute the cost among all participants. Despite the fast-changing landscape in this field, there has been scarce literature on the theoretical underpinning of P2P insurance and mutual aid. This paper presents the first effort to build a unified framework to quantify and assess the exchange of risks in a network of participants from different risk classes. Under this framework, the paper aims to address several essential research questions, including the fair exchange of heterogeneous risks and the optimality of algorithmic designs under various criteria. The modeling of multi-risk exchange is done with a P2P network structure. We show that these network structures not only can be used to explain the current practice in the industry, but also provide new tools to develop better designs. The paper concludes with a comparison of traditional insurance and P2P risk sharing from the standpoint of stability and cost reduction. Author Affiliation: Department of Mathematics, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA * Corresponding author. Article History: Received 23 June 2020; Accepted 14 September 2021 Byline: Samal Abdikerimova [abdiker2@illinois.edu] (a), Runhuan Feng [rfeng@illinois.edu] (*,a)