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Warehouses represent key links in domestic and international commodity flows. The increasing shortage of workers and increasing costs on the one hand, and the increasing number and stricter demands of users on the other hand lead warehouse managers to realize their operations as efficiently as possible. A proposed model has an objective of enabling companies to monitor warehouse performance in an authoritative, reliable, and simple way and define appropriate corrective measures accordingly. The proposed empirical research consists of three stages, where in the first stage a combination of Principal Component Analysis-Data Envelopment Analysis methods was applied in order to determine efficient warehouses based on 90 decision making units. In the second phase, a completely new method called Interval Fuzzy Rough Pivot Pair-wise Relative Criteria Importance Assessment method used for determining criteria weights was developed and applied, which is one of the most important novelties of this study. In the last phase, the Interval Fuzzy Rough Measurement of Alternatives and Ranking according to the Compromise Solution method was applied to rank the alternatives. Twelve criteria were observed to evaluate 21 alternatives. Based on the results, it was concluded that salary stood out as the most important criterion, while amortization stood out as the least significant criterion. On the other hand, alternatives A9 and A10 stood out as the best-ranked alternatives while A1, A2, and A3 stood out as the least efficient ones. The paper provides clear scientific contributions that are reflected in the reduction of the gap that was observed after reviewing the literature where there is a lack of papers dealing with this task. Also, the combination of methods applied in the paper has not been used so far, so it can be said that this paper represents an excellent basis for further research. The model has practical contributions as it allows decision-makers to make quality decisions regarding the operation of their warehouses in different time periods or observation periods, as well as it represents a decision support tool that can be used for better warehouse management. • New model for warehouse performance evaluation has been proposed. • An integrated PCA-DEA-IFR PIPRECIA-IFR MARCOS Model was developed. • New approach IFR PIPRECIA was developed and presented in literature for first time. • The model enables more accurate and precise decision-making in logistics. [ABSTRACT FROM AUTHOR]

Industry 4.0 (I4.0) has emerged as a highly innovative response to market needs, particularly in logistics. This paper presents a structured case study on the implementation of I4.0 technologies for material flow and handling management. The study explores the contextual framework, historical development, and key characteristics of I4.0, focuses on the necessary characteristics for I4.0 certification and outlines the specific features exhibited by the company under study. Objectives include enhanced traceability of metallic materials and optimization of crane management. The paper outlines the project phases, highlighting the positive impact on lead time reduction and providing insights into operational procedures. This research contributes to understanding I4.0 practices in logistics and offers valuable insights for future implementations, driving enhanced efficiency and productivity. [ABSTRACT FROM AUTHOR]

A new harvesting system, delayed harvest, and the fibre properties of RCG (reed canary-grass, Phalaris arundinacea L.) makes RCG an interesting new source of raw material for the pulp and paper industry in northern Europe. Storage and transport are some of the limiting factors for using RCG as pulp raw material. The cost of transportation and storage is strongly related to the density of the raw material. To be able to guarantee year round available raw material to pulp mills, the logistic problems must be solved. This study examines low-density briquetting of RCG to improve logistics. To evaluate if the conditions in the briquetting process caused fibre damage, the properties of pulp from briquetted material was compared to those of pulp from non-briquetted material. Pulp produced from briquetted RCG had more fines as compared to the non-briquetted reference material. Hand sheets produced using pulp from briquetted RCG were thinner, denser, and had lower air permeability compared to the non-briquetted reference material. The strength properties of pulp made from briquetted RCG indicated little or no difference compared to the reference material. Briquetting of RCG can increase transport capacity, by taking full advantage of maximum load permitted on the vehicle. This improves the transport economy considerable. [Copyright &y& Elsevier]

Supply chain problem of a large international pulp producer with five pulp mills located in Scandinavia is studied. The company currently uses manual planning for harvesting and transportation of pulp, production scheduling, and distribution of products to customers.

Frequently, various sectors within the same company often find themselves at odds with one another due to conflicting objectives. For example, the sales and logistics departments frequently fail to synchronize, with sales viewing logistics merely as a cost center. Conversely, sales place demanding delivery tasks on logistics, particularly evident in scenarios involving out-of-stock or non-assortment items. To address this pervasive issue, the primary objective of this paper is to propose a model for assessing the efficiency of logistical processes, distribution centers, and drivers. Hence, it can be asserted that this study, through its proposed model, aims to accomplish several aims: (i) determine the effectiveness of distribution centers (DCs), (ii) analyze how the efficiency of DCs evolves over time, (iii) evaluate the performance of distribution drivers, and (iv) rank proficient drivers for bonus allocation based on their performance. To achieve these objectives, the suggested model relies on the application of the CI-DEA-Malmquist Index-DEA-MEREC-ADAM methodology. Specifically, the model is delineated into three distinct phases. The initial phase entails employing the CI-DEA and Malmquist index methodologies to condense the multitude of parameters considered in the study by utilizing the CI-DEA approach. Additionally, Malmquist analysis is applied to observe the multi factor productivity change in the efficiency of DCs and to identify the most efficient DC across all time periods. Following the identification of the most efficient DC, the subsequent phase focuses on selecting drivers from that center, followed by applying the DEA method to isolate only the most efficient drivers, who are then further evaluated and ranked accordingly. Through the application of these methodologies, it was determined that out of a total of 10 drivers, only four were deemed efficient. In the final phase of the model, these drivers were assessed based on seven criteria for ranking purposes. During this phase, the MEREC method was utilized to ascertain the criteria weights, while the ADAM method was employed for driver ranking. The findings revealed that the second driver ranked the highest and thus should be granted the highest bonus. [ABSTRACT FROM AUTHOR]

Analysis of the accessibility impacts of logistics suburbanization is critical for logistics land-use planning practices. To understand these impacts, this paper conceptualizes logistics service accessibility from two perspectives in terms of urban logistics infrastructure networks (ULINs) and logistics land use stakeholders in the network, and proposes a novel quantitative approach for their measurement. We measure the service accessibility of ULINs via solving a bi-objective binary integer program which considers the facility spatial coverage and vehicle path planning. Further, cumulative-opportunity freight accessibility models are proposed to measure the service accessibility of logistics land use stakeholders while accounting for their different logistics demands. The proposed method is capable of measuring the spatiotemporal impacts of logistics suburbanization on the service accessibility of ULINs and the corresponding stakeholders. We use the real data of Beijing as a testbed and our results reveal that (1) there is considerable variation in the service accessibility of ULINs and logistics firms' service accessibility with respect to different logistics facility locations and (2) choosing logistics facilities' locations requires careful consideration of the differences in ULINs' service accessibility to mitigate uneven service availability on the receiving side. The paper highlights the potential for freight accessibility in urban freight planning and provides effective quantitative evaluation approaches to support better practices in logistics land use and transport planning. • Logistics service accessibility has been conceptualized from two views of infrastructure network and land-use stakeholders. • Infrastructure-based freight accessibility model has been proposed to measure the service performance of ULINs. • The impacts of logistics suburbanization on the service accessibility of ULINs, goods suppliers and receivers are examined. • Policy suggestions for planning attractive logistics facility locations to encourage logistics clusters are provided. [ABSTRACT FROM AUTHOR]

The paper deals with the extension of the logistics simulation within an agent-based simulation framework to be able to consider the delivery across several supply chains. The logistics simulation is placed in the context of the underlying freight transportation simulation. The use of multiple possible logistics chains addresses a key limitation of previous studies. Logistics chains represent the various transportation options of a Logistic Service Provider (LSP) and are made up of resources such as depots, logistics hubs and carriers that the logistics service provider can commission. When implementing the new functionality, the existing flow of the simulation process must be considered. In particular, changes need to be made to the assignment of freight requests to logistics chains, the iterative optimization of this assignment and scheduling. Appropriate assignment methods and rescheduling strategies are developed and presented. These innovations reveal compatibility problems within the existing simulation framework. The functionality developed is presented in constructed scenarios, highlighting the advantages of using multiple logistics chains. In addition, the applicability is demonstrated in a comprehensive real scenario that includes the delivery of supermarkets. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to critically review the current available (large/SMEs) Maturity Models (MM) for Industry 4.0 (I4.0) adoption in manufacturing and logistics sectors, as well as recognize the specific requirements of SMEs for a MM adoption. In total, 16 MM were studied with various scopes, where 5 studies applied on SMEs. To this end, this paper identified manufacturing SMEs specific requirements, conducted a review of current MM, and identified the main MM scopes for SMEs and large enterprises as well. This study found that Smart Manufacturing, Smart Supply Chain (SC), Product Development, Digitized Data collection & Analytics, Technological Infrastructure, Smart Logistics, Performance Evaluation, and Employee participation are the main scopes used for SMEs. [ABSTRACT FROM AUTHOR]

The growing complexity of the logistics chain, the need to take on an ever longer and distributed logistic chain, which in some cases even reaches the final stages of the production of the same goods, highlights the problem of managing the post-production phases of products and goods, but also of the personnel who work on these activities, charged to the companies that deal with logistics. We present in this paper the Integrated Logistic Platform (ILP 4.0), a software architectural model, whose purpose is to lead warehouse logistics to new levels of efficiency, not reachable as the sum of the operational functions within a single logistic company, but reachable only through a unique and cross-functional system, which surpasses the usual fragmented vision and consequent approaches, in favor a strategic coordination of all activities. In this paper it is described the general architecture of the realized platform, with its research contributions and innovations, in particular related to some typical problems of warehouse environments, solved with the help of machine learning and computer vision approaches, but also with the integration of augmented reality (AR) and virtual reality (VR) devices. The aim of the integration of these technologies in the project is the definition of a "smart" warehouse model environment, capable of mitigate problems of warehouse logistics such as: automation of the inventory process (through an UAV), control of warehouse movements, and management of logical / physical security of the premises. Based on the experiences made on the project, and focusing the attention on the safety and security aspects in logistics, that the platform covers, we discuss further a possible federated learning approach in order to mitigate the lack of data in order to solve some security and safety problems in the logistic area. [ABSTRACT FROM AUTHOR]

The importance of supply chain management is paramount nowadays and this research seeks ways for better supply chain coordination. We present a roadmap for implementing true digital replicas of physical supply chains based on a disruptive simulation modeling approach. These digital replicas can enable the comparative evaluation of existing Just-In-Time (JIT) control policies for the first time without the unrealistic assumptions of existing studies in the literature. These realistic supply chain simulation models have the prospect of giving us better understanding of their behavior and of their complex dynamics. We provide guidelines for using the digital replicas and advanced optimization approaches to derive novel supply chain coordination policies pushing the field of JIT control beyond the state-of-the-art. An equally important contribution of this research is that it advances the field of hybrid discrete event-system dynamics (DES-SD) simulation with the prospect of pushing Systems Engineering to the next level. This research discusses theoretical foundations for mixing DES with SD simulation, and explores technical aspects and implementation details. The implications of this extent well beyond the supply chain field since both DES and SD have dozens of application areas including manufacturing, service systems and economics, social sciences, respectively. The paper is concluded with a discussion on the potential impact of the proposed approach including insights for practitioners, applicability of scientific results in industry and prerequisites for business process re-engineering. [ABSTRACT FROM AUTHOR]

Stocktaking refers to the examination or counting over of materials, supplies, goods or products inside a stockroom, store, warehouse. There are many challenges concerning this important business function, which are even more demanding inside an unstructured large warehouse. Huge variance in size, volume, shape of the stock-keeping units that are stored in bulk without packaging, leads to many emerging problems that necessitate significant research endeavors so as to develop solutions that can automate this process. Nowadays, there are many approaches related to computer vision-based stocktaking in unstructured warehouses with products stored in bulk, which employ several existing technologies namely Deep Learning, Optical Character Recognition, and 3D model retrieval. The paper at hand aims at presenting the i-Count Air concept which outlines the utilization of Unmanned Aerial Vehicles, endowed with cognitive hardware sensors, active vision and an innovative perception and stocktaking software, that will push the boundaries of robotic perception and help automate the inventory counting function in a Warehouse 5.0 environment. [ABSTRACT FROM AUTHOR]

This research paper examines the evolution of human-machine interfaces (HMIs) in the manufacturing and logistics sectors in the context of Industry 5.0 (I5.0). I5.0 introduces a human-centered paradigm, and as digitalization transforms processes in these domains, human-machine interaction is undergoing a notable shift. Yet, there is a lack of I5.0 HMI requirements and design guidelines. Through a literature review, the research identifies and investigates general requirements for HMIs in I5.0. Findings include ethical principles, ergonomics, adaptability, human-centered design, intuitive interaction, and effective collaboration. It also uses a case study approach to highlight potential strategies and discuss challenges. The results provide valuable insights into considerations for designing effective HMIs for I5.0 applications, enhancing the user experience, improving productivity, and facilitating successful human-machine interactions. [ABSTRACT FROM AUTHOR]

In the modern business world, where hybrid business processes are widespread, effective resource and operations management defines the success of companies. One of the most critical areas is logistics, which is a critical component for many organizations, regardless of size or industry. The management of logistics processes is becoming more complex every year, as the demands on the industry are becoming more complicated and today consists not only of efficiency issues but also of environmental friendliness, and globalization. In this situation, RPA technology is one of the main solutions, enabling companies to achieve new levels of efficiency, accuracy, and speed in managing warehouse processes. In this article, we will consider modern approaches to managing hybrid business processes using the example of warehouses and explore how RPA technology has become the main optimization tool. The paper observes specific examples of the use of RPA in the context of warehouse management, identifies the benefits and risks associated with automation, and defines the development prospects and future of this innovative technology in logistics. [ABSTRACT FROM AUTHOR]

Carbon cap-and-trade policy based on market mechanism becomes an important means to restrain shipping logistics enterprises' carbon emission reduction. This paper studies the new requirements of shipping enterprises under the pressure of carbon emission reduction. Considering the logistics service supply chain composed of two competing providers and one integrator under the constraint of carbon cap-and-trade policy, this paper explores the optimal pricing and revenue decision of shipping logistics service supply chain through vertical cooperation, horizontal cooperation between providers and revenue sharing cooperation among integrators. This paper obtains feedback strategies under different cooperation modes by constructing a game model. In the vertical game, the shipping logistics supplier is the Stackelberg leader, and the shipping logistics integrator is the follower; there is a Nash equilibrium in the emission reduction decisions among suppliers in the horizontal game. On this basis, the results of different cooperation modes are compared, and the influence of competitive strategies on the optimal results is discussed. We found that the vertical cooperation of the shipping logistics service supply chain has a higher carbon emission reduction rate and a lower sales price, and the horizontal cooperation of shipping logistics suppliers can improve their own profits but reduce the income of the shipping logistics integrators and consumer welfare. When the revenue sharing contract provides the shipping logistics integrator with a share proportion in a certain range, the revenue sharing contract can generate higher supply chain profits than the integration of two chains, which can urge shipping logistics suppliers to forfeit the horizontal cooperation and help the shipping logistics service supply chain achieve win-win results. [ABSTRACT FROM AUTHOR]

This paper studies the relationship between logistics, intermodality and airport efficiency. To this end, using Data Envelopment Analysis (DEA), the efficiency of the 21 largest European airports has been estimated over the 2009–2014 period. In a second stage, this research analyses the effect of Logistics and Modal Integration on airport efficiency. The airport's ability to compete globally depends, greatly, on the passengers and cargo' access to efficient networks. The results show evidence of the positive impact of the quality of the national logistics system on Airport efficiency. The effect of Logistics on overall airport efficiency is estimated at 0.15% for every 1% increase in the Logistic Performance (LPI), ceteris paribus. Furthermore, airports that have a direct link to a High-Speed Rail (HSR) network are expected to perform, on average, 27 per cent above the rest of the airports. Finally, airports that offer more facilities to optimise the interface between airport and aircraft are expected to achieve higher efficiency levels. • Airport's ability to compete globally depends on the access to efficient networks. • This paper find evidence of the positive impact of the quality of the national logistics system on Airport efficiency. • The effect of Logistics on airport efficiency is estimated at 0.15% for every 1% increase in the Logistic Performance. • Having Direct link to a High-Speed Rail (HSR) is crucial for hub airports efficiency. [ABSTRACT FROM AUTHOR]

Supply chain and logistics management for spare parts is of key importance in the maritime industry, in order to ensure high availability and reliability of assets, while keeping operating costs in acceptable levels. Supply chain and logistics operations for spare parts incorporate high complexity, uncertainty and costs, due to special characteristics of the maritime sector, as for instance moving assets, globally scattered points of supply and demand, strict time windows and multi-actor setting. Typically, the asset owner purchases spare parts for their vessel from a foreign supplier, and consolidates them in a regional warehouse. Subsequently, these spare parts are shipped to a port using various means of transport such as air freight, sea freight or road freight. Finally, once the vessel calls at subject port, the spare parts are delivered and used on board for maintenance activities. For repairable items, the reverse logistics process also does exist; a spare part is offloaded from a vessel, repaired and then re-delivered on board. Efficiently handling such a logistics network constitutes a great challenge, nevertheless, this topic has received little attention in the literature and a systematic review is currently missing. In this paper, the authors attempt to address this research gap by performing a systematic literature review on spare parts supply chain and logistics management in the maritime sector. To achieve this objective, after applying the defined inclusion and exclusion criteria on the initial search results, a set of (30) eligible papers, participating in the review, has been identified. These selected papers are illustrated and discussed in detail, with the purpose of addressing the research questions initially set by the authors. Fundamentally, this study aims to describe the current state of the art in the subject area, identify existing challenges and trends, and finally provide suggestions on future research. We aspire that the results of this review can be used as the foundation for future research on spare parts supply chain management in the maritime sector. [ABSTRACT FROM AUTHOR]

• Demand responsive freight deliveries are optimized with TSP tour length approximations. • Headways and zone areas for flexible‐route delivery systems are jointly optimized and closed‐form solutions are obtained. • The problem is reformulated as a Lagrangian relaxation problem to constrain an integer fleetsize. • The single‐zone model presented in this paper can be the modular basis for a multi‐zone model with possible freight flows among all zones. • The sensitivities of results to important input factors are analyzed. Freight delivery planning is a critical area in transportation and logistics. This paper presents a planning-level model for jointly optimizing headways and zone sizes for flexible-route freight deliveries. The model analyzes deliveries for a one-to-many demand pattern from one terminal to random destinations in a zone, which are reached through approximated travelling salesman problem (TSP) tours. Then, the problem is reformulated as a Lagrangian relaxation problem to constrain the fleet size to an integer value. The proposed model and closed-form solutions provide direct insights into the relations affecting those decision variables. Results from the base case study and sensitivity analyses indicate how various factors affect optimal service frequencies, delivery zone sizes, and costs of freight deliveries. Before detailed vehicle routing problems (i.e., actual delivery scheduling and operations) are solved, the proposed model should be useful for planning freight delivery systems, regarding critical decisions about geographic coverage of services, delivery frequencies, vehicle capacities, and other system characteristics. The developed model can also be used for pickups with a many-to-one demand pattern and extended to serve many-to-many demand patterns in multiple delivery zones through transfers at a central terminal. [ABSTRACT FROM AUTHOR]

The offshore wind industry is advancing with larger turbines (10 MW+) into sites in deeper waters (>60 m), necessitating innovative floating substructures. However, Floating Offshore Wind (FOW) must still be proven to be cost-efficient, with special attention paid to developing installation, Operations and Maintenance (O&M) and decommissioning strategies that will ensure FOW is competitive. Simulation is an efficient way to assess the viability of new technologies and the innovative operations required to install and maintain them. This paper presents a novel tool that simulates the installation of fixed/floating offshore wind farms across an hourly time-series of Metocean data, producing a total estimation of costs as part of the total capital expenditure (CAPEX). The paper validates the model by simulating installation of Hywind Scotland, the FOW farm, and comparing results with published data. Given the lack of real-world cost data and experience, this paper then seeks to provide a well-defined case-study for future researchers to develop further in other regions and with different technologies. The tool is applied to a theoretical large commercial 1GW FOW farm commissioned in 2035 at a representative site in the Celtic Sea. This considers a promising location for FOW development outside the existing demonstration/early commercial FOW projects, which are primarily focused on the North Sea. Results indicate a CAPEX (including installation) of €3492/kW, which is in line with industry expectations. Sensitivity analysis applies a learning rate to reduce platform costs, and varies farm capacity, demonstrating the potential economies of scale when increasing farm size. Simulation identifies weather operational limits and cable installation duration as key contributors to installation time and costs. This quantifies where cost-savings can be found and optimisation should focus. Further modelling considers the scale of their impact on results. A final Levelised Cost of Energy assessment estimating an LCoE range of €52.3–64.59/MWh, placing the FOW farm in the context of global economic targets. • Novel installation tool for fixed/floating offshore wind farms. • Tool validated for floating wind against installation data for Hywind Scotland. • Provides reference case-study with full input details to promote re-use. • Installation costs are sensitive to weather operational limits and durations. • Results: LCoE of €52.3–64.59/MWh for floating wind farms in the Celtic Sea, 2035. [ABSTRACT FROM AUTHOR]

• This paper studies an application of the DVRPTW for IoT customers' dynamic demands. • This paper develops a method of re-optimization based on time slices. • This paper constructs a mathematical model with the goal of minimizing distance cost. Developing a more convenient and sustainable logistics delivery operation model has become a consensus need for both academics and practitioners. However, the existing literature has focused on the impact of dynamic features of IoT customers on the distance cost of vehicles (DCV) and quantity cost of vehicles (QCV) in the field of the vehicle routing problem with time windows (VRPTW). Moreover, only a few application scenarios have been considered. This paper focuses on the perspective of intelligent logistics development to research the impact of IoT customers' dynamic demand on the VRPTW. A mathematical model is established to respond to the dynamic demands of IoT customers with the goal of minimizing the distance cost. A strategy for solving the dynamic VRPTW (DVRPTW) based on time slices is developed, and an improved tabu search (I-TS) optimization algorithm is proposed to solve a given delivery business case. In simulation experiments, the proposed I-TS solution and another known best solution (namely, Solomon) are compared, and the results show the superior performance of the I-TS algorithm in reducing the DCV and QCV. Furthermore, the case study explores the relationship between the degree of dynamism (DoD), DCV and QCV under two scenarios (responding and not responding to dynamic demands of IoT customers). It is concluded that fluctuations of the DoD in a certain range affect only the DCV and not the QCV. Large-capacity vehicles can improve the robustness of the route scheme to dynamic demands. In addition, decomposing dynamic issues in space through time slicing effectively reduces the complexity of the DVRPTW solution. This research also aims to assist practitioners in better formulating dynamic delivery routes as well as policy makers in developing intelligent delivery operation models. Finally, limitations and future research directions are discussed. [ABSTRACT FROM AUTHOR]

• A special issue on "technology-driven logistics and supply chain management for societal impacts" • 14 research studies discussed and categorized under technologies, ESG, and platforms. • A discussion paper is presented based on the studies in the special issues. • Five future directions derived. In recent years, there has been substantial growth in the utilization of technologies within the logistics and transportation industries. This growth has resulted in the emergence of numerous novel and exciting applications, offering researchers valuable opportunities to develop innovative solutions. The field of operations management is well-positioned to contribute significantly to this development and promote socially responsible values. This paper investigates the impact of technology-driven logistics and supply chain management on various aspects of social values, categorized as technologies, platforms, and environmental, social, and governance (ESG) considerations. Additionally, it provides an introduction to the papers featured in this special issue. Lastly, the paper proposes future research directions to further advance the societal impacts of technologies in logistics and transportation applications. [ABSTRACT FROM AUTHOR]

Health planners charged with the task of building or at least maintaining the health of populations within low- and middle-income countries (LMICs) have to find ways of providing steady, predictable supplies of health commodities for unpredictable demands for healthcare and health. To address this issue, this paper emphasizes a focus on aggregate commodity security defined as the continuous interrupted supply of health commodities belonging to all therapeutic categories and not just a selected subset. Given this focus, the paper identifies logistics systems comprising of a set of logistics activities as the machinery for assuring aggregate commodity security. Steady reliable supplies of health commodities, whenever and wherever they are needed, however, means looking beyond logistics systems. Health planners must ask whether there is a healthy supplier base for the commodities needed. The paper notes that a secure supply of health commodities in any LMIC, will remain an illusion without functional logistics systems supported by a healthy supplier base. [ABSTRACT FROM AUTHOR]

With the increase in the number of avenues for production of data everywhere including logistics, using this data has become an obvious next step. In this paper, we look at the major logistics problems in details as discussed in a seminal work in highlighting the problems in logistics by X. Li in 2014. Together with discussing the problems, we also look at the trends in solving these problems using machine learning. We look at the recent work done in the particular fields using machine learning (ML) and develop the correlation of the trends of using supervised, unsupervised and reinforcement learning in solving these problems. This correlation is developed using a table and a diagram showing ML techniques and the trends in the fields of the problems are discussed. COVID-19 has greatly accelerated these trends. This paper serves as a gentle introduction to ML techniques in the field of logistics for researchers who are new to the field. [ABSTRACT FROM AUTHOR]

A supply chain's ability to avoid an unexpected disruption or quickly return to a normal situation defines supply chain resilience. Prior works have emphasized the integration of supply chain resilience and sustainable development goals (sustainable supply chain resilience), which is the focus of this paper. This paper proposes a four-level supply chain consisting of suppliers, intermodal hubs, manufacturers, and distributors along with a heterogeneous fleet of vehicles. Two types of manufacturers are included: large and small. The small manufacturers are moveable. To contribute to sustainable logistics problems, the objectives are cost, carbon emissions, and job opportunities when the appropriate supply chain members and flow of materials are optimized. To contribute to supply chain resilience, this paper presents a new robust approach and a new multiobjective algorithm to capture uncertain parameters (e.g., supply cost and employee availability). A numerical example based on empirical data shows the applicability of the proposed model. • This paper proposes sustainable supply chain resilience. • A heterogeneous fleet of vehicles and manufacturers are considered. • A new robust approach is introduced. • A new multiobjective algorithm is proposed. • Datasets along with algorithms codes are available for journal readers. [ABSTRACT FROM AUTHOR]

• Analysis of logistics performance impact on natural environment in EU countries. • Methodology of Green Logistics Performance Index (GLPI) creation to compare countries. • GLPI components: Logistics Performance Index and Environmental Performance Index. • GLPI calculation for EU countries to compare, and see the progress or regress. • Overview on GLPI as a benchmarking tool with its utility suggestions. Logistics performance has a significant impact on the natural environment. The paper analyses it from a broad macro perspective of European Union countries. Also, it proposes the methodology of creation and possibilities of use of the Green Logistics Performance Index (GLPI) to deepen the analyses and compare countries. The paper's primary goal is to introduce and justify the implementation of the GLPI. First, a literature review is provided, covering the concept of green logistics and environmental problems. Next, the Logistics Performance Index (LPI) and Environmental Performance Index (EPI) are described in detail as the components of GLPI, and the methodology of GLPI creation is presented. Finally, the GLPI is calculated for all European Union countries in 2018 (the latest data) and 2010 to compare the differences and see the progress or regress. This part of the paper gives an overview of GLPI as a benchmarking tool, pointing out the positives and negatives, and transferring the best environmental practices from leading counties to others. In the end, the benefits of GLPI are described together with its utility suggestions. [ABSTRACT FROM AUTHOR]

This paper examines the current organisation of Hotel-Restaurant-Café/Catering (Ho.Re.Ca.) logistics in medieval structured cities from a microeconomic perspective. The paper aims to distinguish Ho.Re.Ca. specific cost generators and to provide different stakeholders with guidelines on improving the efficiency and sustainability of delivery operations. Therefore, a Ho.Re.Ca. specific costs function has been developed and calculates both internal (economic) as external (social and environmental) costs. The developed cost function follows a 3-steps approach: exploratory expert interviews and observations, the development of the cost function and, validation by the same business experts. The main findings are that mostly the characteristics of the goods determine the way Ho.Re.Ca. goods are delivered nowadays. However, the location of demand and supply for the goods and the specific handling conditions also have a significant influence. The following specific cost generators are distinguished: all labour-based activities rise the internal costs structures substantially. Congestion and city quality issues are identified as major external costs generators. Originating from these results, transport operators should focus on improving labour-based activities such as the service time by investing in e.g. innovative (un)loading equipment. For governments, the internalisation of congestion-related externalities by e.g. road pricing is decisive. [ABSTRACT FROM AUTHOR]

Decision support systems are becoming increasingly sophisticated (e.g., being machine learning-based), attempting to automate decisions as much as possible. However, it remains challenging to extract meaningful value from large quantities of data while also maintaining transparency in seeking justification for the choices made. Instead of creating methods for increasing the interpretability of black box models, one way forward is to design models that are inherently interpretable in the first place. Rule-based methods can automate decisions with great transparency and accuracy, helping to ensure compliance with regulations and adherence to organizational guidelines. In this paper, we propose an approach that uses a decision tree machine learning classification technique for extracting business rules from IoT-generated data to predict the asset status of Smart Returnable Transport Items (SRTIs). We report on an industrial case study that uses two years of historical data, obtained from an SRTI provider in the Netherlands, to predict the status of smart pallets. We compare the performance with the results obtained by using a support-vector machine (SVM) technique. Our experiments show that our solution is both accurate and flexible in terms of business rule elicitation. The obtained decision trees are human-interpretable, can easily be combined with other decision-making techniques, and provide a prediction accuracy marginally higher than an SVM technique. [ABSTRACT FROM AUTHOR]

Drugs shortages have become a major issue affecting healthcare systems worldwide. With the growing use of electronic records, data analytics techniques have been identified as a major asset to provide support in managing pharmaceutical supply chains. However, applications addressing drugs shortages, which arise from various complex factors, are still expected. Therefore, this paper investigates whether the use of logistics data at the national level can provide insights into drugs supply disruptions issues. Basic features were defined from a dataset of 1.281.545 electronic data interchange records between French hospitals and drugs distributors in 2021. Additionally, anomaly detection and correlation analysis were performed to (i) detect supply disruptions of four products in 2021; and (ii) assess whether the features defined can be used in future time series predictive models. Findings highlight a promising opportunity to harness these data through more advanced analytics techniques to anticipate and manage drugs shortages at local, national, and European levels. [ABSTRACT FROM AUTHOR]

This paper proposes an optimization framework to deploy a large satellite constellation. The proposed framework consists of two phases: the mission viability evaluation phase and the optimal planning phase. The feasibility of the constellation deployment architecture with given resources is assessed in the first phase. The second phase uses mixed-integer linear programming to optimize the satellite deployment plan based on a dynamic logistics model. The effectiveness of the proposed framework is demonstrated through a case study for optimal deployment planning of a large satellite constellation. • Optimization framework for deploying satellite mega-constellation proposed. • Viability Assessment and Optimal Planning phases comprise the framework. • Direct/indirect injection strategies with primary/auxiliary launchers considered. • Deployment cost and cumulative utility are considered as objectives. • A realistic case study for mega-constellation deployment conducted. [ABSTRACT FROM AUTHOR]

The second in a series of two, this paper conducts a review of the public-sector initiatives that could be used to improve freight activity in metropolitan areas, collects data about the initiatives that have been implemented and their performance, and produces a ranking of suggested initiatives. The review of public-sector initiatives is based on a comprehensive analysis of their performance, which cataloged the initiatives into seven major groups, 15 subgroups, and 48 unique initiatives. The initiatives covered in this paper include: Financial Approaches; Logistical Management; and Demand/Land Use Management. The characterization of the state of the practice, and the performance of the initiatives, was based on a survey that collected data from 32 countries and 56 cities throughout the world. The third component of the work consisted of the generation of a ranking of suggested initiatives based on the performance data collected by the survey. The fourth component of the research reported here is the development of a process intended to lead to the sustained improvement of urban freight management. The paper ends with a discussion of chief findings. [ABSTRACT FROM AUTHOR]

Tracking of dynamic objects is a key element especially for in-door logistic solutions but also for e.g. manufacturing plants and warehouses. This paper is dealing with a tracking approach which is based on multiple cameras that are permanently mounted on the ceiling. In comparison to currently applied methods of detecting and tracking dynamic objects in the field of AGVs this approach is innovative. This is due to the shift in the capture of tracking data to ceiling cameras exclusively, for the reason of gaining a holistic overview of the complete tracking area. The application case discussed in this paper is for AGVs in the frame of a research project. However, this approach can be applied for different use cases which require a pursuit and tracking of dynamic objects that is based on multiple cameras. [ABSTRACT FROM AUTHOR]

In this position paper, we summarize history, current activities and future topics of IFAC Technical Committee (TC) 5.2 "Manufacturing Modelling for Management and Control". As a special focus, we discuss the results of the 9th IFAC Conference MIM 2019 that was recently organized by IFAC TC 5.2 in Berlin, Germany and attended by 740 participants. We analyse the current activities of the working groups within TC 5.2 and project some future research directions. Finally, we present an overview of papers from TC 5.2 in this special issue. [ABSTRACT FROM AUTHOR]

The paper suggests a novel workflow to solving adaptively the automated guided vehicle (AGV) fleet management problem with the key objective to serve production flawlessly. Departing from a material flow network model it is shown how an analysis using recent notions and methods of network science can detect the hidden structure of the overall problem. Once uncovered, this modularity-based structuring is exploited when balancing the expected load of vehicles and dynamically deciding their final dispatching. The paper presents stages of the workflow and the merits of its application on a series of comparative simulation studies taken from industrial experience. [ABSTRACT FROM AUTHOR]

• Uses GPS data for measuring travel time reliability. • Measures travel time reliability from a freight fluidity perspective. • Delivers insights to public and private decision makers. Travel time reliability is one of the most important assets when it comes to designing and assessing freight fluidity of transportation systems. Guaranteeing reliable delivery times is, according to different international studies, a strategic competitive advantage. Nonetheless, emerging countries such as Mexico, do not currently count with specific indicators to measure travel time reliability from a freight fluidity approach. As such, there is no clear measurement of the impact and propagation of the variability of transit times throughout the supply chains. Since road transportation is the main mean of transportation in emerging countries, the aim of this paper is to present the analysis carried out to measure the travel time reliability thanks to different methodologies based on freight data collection using GPS (Global Positioning System), as a key element to assess freight fluidity in freight transportation corridors. The analysis measured items such as: (i) percentiles of travel time; (ii) planning time index; (iii) buffer time index; (iv) skew and range of travel. Different probability distributions were analysed and the distribution of travel time data was determined through statistical hypothesis test. The conclusion was that distributions with upper tails longer than usual fit better to the collected data. Evidences of mixture distributions in the travel time data were also found. Finally, the paper also presents useful conclusions to develop future research as well as to improve practices for decision makers. [ABSTRACT FROM AUTHOR]

The importance of electric vehicles (EVs) lies in the fact that they are seen as a key solution to the climate change problem. In the last decade, this topic has received significant interest from the scientific community, contributing to publications in different areas. However, the existing literature is fragmented, and efforts have not been made to categorize and analyze it from a freight logistics perspective. This work aims to fill this gap by presenting a systematic literature review (SLR) of the potential impacts of EVs on sustainable road-freight transport operations, including in urban areas. We reviewed 237 peer-reviewed articles for bibliometric and literature classification analysis, whereby 119 articles were subsequently studied for content analysis and research gaps related to sustainability approaches. The bibliometric analysis showed significant growth in the body of research in the past two years, reflected in the number of journal papers, authors, and references. In the literature and keywords analysis, we identified five main categories and research areas: economic and competitive aspects, city logistics, environmental sustainability, vehicle fleet operations, and infrastructure and technology. In addition, this paper revealed eight key research gaps for future research: multimodal integration, long-haul and heavy-duty truck approaches, emerging economies, business models, social factors, charging infrastructure inclusion, and fleet replacement policies. These findings can enlighten researchers and practitioners toward sustainable research and real-life applications of electromobility in freight logistics. [ABSTRACT FROM AUTHOR]

In the oil and gas industry, there is a need for constructing auxiliary maintenance and storage buildings nearby exploration sites. As the initial stage for such constructing purposes, it is required to drill wells for construction piles. To this end, there is a fleet of mobile drilling rigs traveling from one exploration site to another, performing the work on drilling wells. For each site, we have a time window for completing all the work on drilling. To complete all the work among all the exploration sites in time, it may be necessary to allow several drilling rigs to perform work at the same site. Yet, in the real world, unforeseen circumstances can affect drilling time, and that, if disregarded, can lead to a disruption of the work plan. Thus, in this problem, we maximize possible deviations of drilling times from expected values when there is still a feasible solution to perform all well-drilling requests in time. At the same time, total traveling costs must be no more than a given threshold. It is a so-called threshold robustness approach. The described Drilling Rig Routing Problem (DRRP) differs from other well-studied variants of Vehicle Routing Problem (VRP) in that the work splitting affects the service time. There is a limited number of papers dealing with such problems and no papers about the robust formulation for them. This research proposes a mathematical model for the novel formulation of the DRRP with uncertainties and an Adaptive Large Neighborhood Search (ALNS) algorithm to solve it. The destruction operators work either at the route, customer, or visit level. The reconstruction operators take into account a possibility to change the work partition. Computational results for the algorithm and Gurobi solver show the dominance of the ALNS scheme for medium- and large-sized instances. • Mixed-integer linear programming model is proposed for the robust optimization. • Adaptive large neighborhood search is adapted considering split service aspect. • The number of destruct and repair operators to use is optimized. • Comprehensive computational experiments are provided. [ABSTRACT FROM AUTHOR]

This paper aims to provide a current status of the legal situation necessary due to the regular changes of the law of the EU and Germany, by identify technical and legal critical success factors of the feasibility of drones and AGVs in last-mile-delivery. Furthermore, the paper provides importance rankings for legal and technical critical success factors from the point of view of logistics and supply chain experts. A conceptual model was developed capturing main legal and technical critical success factors from literature finding and then providing basis to a survey-based study that have been captured online. Results from the survey were evaluated and compared against each other using the Analytical Hierarchy Process. The results are based on business-to-business relationships between logistics service and mobility providers, as well as technical developers. The results of this research can help managers of large providers, transport companies in general and governments as well as political decision-makers in the innovation field to understand the legal situation of the EU and Germany as well as the technical problems that have to be overcome to profit from future technology in the last-mile-delivery. [ABSTRACT FROM AUTHOR]

This paper investigates pervasiveness effect of information technology on the technological progress of logistics in China. Using panel data of 30-regions in China during 2008 to 2020, we propose both static and dynamic panel data models, and find both resource level and spreading rate of information technology have negative influences on technological progress of logistics. The resource level of information technology has a short-term effect on technological progress of logistics, whereas the spreading rate of information technology has a long-term effect. Moreover, the result reveals that the discordant problem of information construction of logistics between resource level and spreading rate cause the negative influence of information technology. [ABSTRACT FROM AUTHOR]

The long-distance cold chain transportation of fresh products from the place of origin to sale is costly due to the high probability of spoilage and high carbon emissions. The potential factors for the high cost of long-distance cold chain transportation are the spoilage of fresh goods caused by transportation vibration and the carbon emission caused by refrigerant use. How to minimize the impact of these factors through optimal transportation route planning is the current problem to be solved. Firstly, a longdistance cold chain logistics route planning model including goods spoilage cost and carbon emission cost is developed, considering the goods spoilage cost caused by transportation vibration and the carbon emission cost generated by refrigerant as well as several other factors. Secondly, an improved ant colony algorithm is used to solve the optimal solution of the model, and the algorithm is redesigned for the characteristics of the model. Thirdly, the pheromone update mechanism in the ant colony algorithm is improved by adding pheromone coefficients to accelerate the convergence speed of the algorithm. Finally, the validity of the model is verified by an arithmetic example. The model and method proposed in this paper help to reduce the cost in the process of long-distance cold chain transportation and bring practical application value. [ABSTRACT FROM AUTHOR]

The location-routing-inventory problem (LRIP) is essential to cold chain logistics (CCL). To solve the problem, this paper proposes an integrated LRIP model considering the carbon transaction mechanism, which simultaneously optimizes the costs associated with location, transportation, inventory, and carbon transaction. The non-dominated sorting genetic algorithm II (NSGA-II) was improved to solve the model. Simulation shows that the improved NSGA-II can effectively reduce carbon emissions of enterprises in the context of carbon transaction. The research offers a solution for reducing total costs in the light of the environmental factors in CCL. [ABSTRACT FROM AUTHOR]

• Effective decision-making for packaging requires an adequate knowledge base. • Comparative studies of single-use and reusable packaging are absent. • Knowledge of logistics effects of large-scale reusable packaging systems is missing. • Food packaging is still evaluated without inclusion of the product it contains. • Shelf life is seldom included in the evaluation of packaging alternatives. In November 2022 the European Commission launched a new regulatory framework proposal for packaging and packaging waste, EU Packaging and Packaging Waste Regulation, which includes mandatory reuse and refill targets of packed food products. With specific focus on perishable liquid food products, such as dairy, plant-based beverages, juices, and nectars, which are currently primarily available in single-use packaging. The purpose of this paper is to provide insights into prevailing knowledge gaps and highlight crucial areas for attention in the ongoing development of packaging solutions that contribute to sustainable development. Based on the systematic literature review of 163 scientific publications, it was found that research into and knowledge of reusable packaging alternatives for primary packaging of perishable liquid foods are clearly insufficient. In particular, there is a lack of knowledge about reusable packaging impacts on food waste and food safety as well as environmental effects of logistics and operational processes. It can be concluded that in any effort to minimise the negative effects of perishable liquid foods, a holistic perspective is crucial so as not to reconfigure packaging for the sake of much higher environmental damages of food waste, or risk consumers' health and well-being. [Display omitted] [ABSTRACT FROM AUTHOR]

Healthcare supply chain management is vital for the adequate and timely delivery of essential medical resources to healthcare facilities. In this context, a machine learning model is proposed in this paper to enhance the service of healthcare supply chains by predicting both the medical supply quantities and its timely delivery. This proposed work utilizes the multi-task learning as both of the interrelated tasks, such as the "shipped quantity" of the medical supplies and its "actual days to delivery", simultaneously optimize their performance to improve supply chain predictions significantly. The prioritized multi-task learning with task-specific regularization provides better learning for the task "actual days to delivery" over "shipped quantity" by considering its significance in healthcare. Additionally, this task-specific regularization also prevents overfitting for the training of the model. The results and its analysis show a significant advancement of 0.3522 and 0.3531 mean absolute error and mean square error for predicting both the tasks. The proposed work outperforms the existing work in terms of mean absolute error, mean square error, root mean square error and R-squared (R 2). In addition, the machine learning interpretation technique is used to assess the contribution of each feature in prediction by the proposed model. • Efficient prediction of medical supply quantities and delivery time in healthcare. • Prioritized multi task learning enhances accuracy as per significance of task. • Task-specific regularization prevents overfitting during training. • Proposed work outperforms existing approaches, enhancing performance. [ABSTRACT FROM AUTHOR]

This paper investigates stakeholder's perspectives about freight congestion in Canada's major metropolitan regions. Interviews with 28 Canadian stakeholders from different sectors are analyzed using Strauss/Corbin extended approach of symbolic interactionism with the objective of producing an explanatory theory to identify barriers to freight in Canada. By integrating emergent categories with a structured framework of theoretical propositions, we are able to offer insights to understand the perceived barriers to goods movement in the Canadian landscape, as well as to detail a framework of interventions to improve freight mobility. In total, 50 themes emerged as barriers to the movement of goods, which were grouped into nine subcategories, and four overarching categories which broadly frame the issues of goods movements as relating to high infrastructure utilization (Infrastructure Demand Outstripping Supply), the cost impacts of diminishing reliability of distribution (Physical Distribution Headwinds Impeding Commerce), rapidly growing regions and ineffective or absent policy support (Urgent Regulatory Encumbrances), and a lack of a robust data collection, analysis, and information sharing framework (Information and Data Management Complexities). These categories were considered in the frame of addressing goods movement barriers and were argued to be influenced by factors of cost, political risk, implement-ability, and maintainability. A framework was developed identifying four high-level interventions: data and knowledge mobilization; public-private collaborative freight evaluations; government funding and political support; and, capacity alterations: improvements and expansions. The key concepts of the framework are to collect and analyze data to inform public-private stakeholder evaluations of policy interventions, with government funding to support both knowledge generation efforts, policy actions and capacity investments. There is a significant need to expand data collection and information sharing, focus infrastructure investments on public transit and intermodal accessibility, and integrated policy development towards transportation and land use planning to address the physical and policy barriers affecting freight mobility and congestion. The emergent theory is contrasted with selected global regions to assess generalizability and the relevance of international perspectives to the Canadian environment. [ABSTRACT FROM AUTHOR]

National logistics cost can be used as a key indicator to reflect a country's overall logistics performance and monitor their respective logistics policies. However, not all countries have developed this indicator, and some have used differing methodologies. This paper provides an approach for calculating national logistics cost per gross domestic product (NLC/GDP) in the context of Thailand and demonstrates its veracity and validity using an action research methodology with key stakeholders. The approach utilizes easily obtainable macro level data combined with survey data. The calculation method has progressively improved in its accuracy and efficacy to reflect Thailand's logistic context. The proposed approach contributes to the national logistics cost debate and can inform academics, managers, and policy makers not just in Thailand but, in other countries when developing their own NLC/GDP to evaluate their respective logistics development activities. • Explains methodology to calculate national logistics cost based on national accounts tables and survey. • Improves accuracy of national logistics costs calculation. • Validates calculation assumptions with empirical survey of 6000 firms. • Confirms individual cost components from previous research. • National logistics cost can be used for Thai government's logistics policy development. [ABSTRACT FROM AUTHOR]

The paper focuses on the fuel transport optimization network for the Total Erg Oil Company to the distribution points sited in a zone near Rome, in Italy. The numerical method is based on a capacitated vehicle itinerary issue for time intervals, considering various heuristic procedures. The fixed and time-dependent travel times are considered. Compared to the standard operational costs, a multivariable objective function is developed that considers: (1) the risk associated with an incidental event involving a fuel tank; (2) that not all the roads are suitable for heavy vehicles transporting fuel products. These two additional terms permit to better quantify the costs for the operator, since it is assumed that roads with higher number of accidents or with not suitable infrastructure conditions have also higher probability of making the fuel tank experiences at least a delay during the day. Results show that a proper vehicle routes design on our multivariable objective function allows economizing about 40 km daily respect to a benchmark. The fuel company can also consider the itinerary design, modifying the weights used with the aim to comprise the additional variables with respect to the standard operational costs, thus assuring a higher safety route planning. [ABSTRACT FROM AUTHOR]

Information technology has promoted the development of globalization, and cross-border e-commerce business has also ushered in rapid development. In recent years, the scale of cross-border e-commerce in our country has grown rapidly, and this industry has gradually become an important component of the import and export trading. Since the cross-border e-commerce business happens between two different countries or regions, there are certain differences in logistics laws, logistics service facilities and human culture in each country or region, so there are many potential risk factors, thus the risks in cross-border e-commerce export trading are also increasingly prominent. Based on the analysis of the market environment risks, customs clearance risks and logistics risks faced by our country's cross-border e-commerce exports, this paper formulates targeted countermeasures combined with the application of big data technology in risk identification, and proposes practical and feasible solutions with preventive advice towards the- cross-border e-commerce export risks in China. [ABSTRACT FROM AUTHOR]

Industry 4.0 and the Smart Manufacturing paradigm are rapidly transforming the way business is conducted in the manufacturing industry. The underlying core technologies of the emerging digital transformation include the Internet of Things (IoT) and data analytics. While the shop floor is the main focus of these paradigms in the narrow sense, it is becoming more prevalent for other companies or business units along the digital supply network to investigate the potential to improve their processes by leveraging these technologies as well. One area that is traditionally reliant on human operators and optimization is the trucking industry. In recent years, this industry has started to explore how the above-mentioned technologies can be utilized to improve their operations, and new policies are further amplifying this process, e.g., by mandating Electronic Logging Device (ELD) to be used by commercial drivers in the USA. This development forces companies to collect digital, high-resolution data – and the question emerges how to utilize this data in the most value-adding way. In this paper, we analyze the current state of the art of digital transformation in the trucking industry by conducting a bibliometric study of recently published papers to identify the main research areas and themes in this field, the leading authors, countries, and journals in this domain. This work will provide the basis for further in-depth studies on optimization techniques and available case studies to provide theoretical input for practitioners and scholars. [ABSTRACT FROM AUTHOR]

• This paper examines the use of mean–variance (MV) theory for risk analysis in global supply chains. • It focuses on the global supply chain operations in the presence of air logistics. • The benefits of blockchain technology on implementing MV risk analysis are explored. • A future research agenda for the application of MV theory is proposed. Supply chain operations have entered the digital era with the emergence of blockchain technology. In this paper, we discuss how the mean–variance (MV) approach can be applied to explore global supply chain operations risk with air logistics in the blockchain technology era. To be specific, we examine the related literature from four areas, namely air-logistics operations, demand management, supply management, and supply-demand coordination. We propose how the blockchain technology can be applied to facilitate the implementation of mean-variance risk analysis for global supply chain operations. We then highlight several promising areas for further studies. A future research agenda is developed. [ABSTRACT FROM AUTHOR]

Highlights • Both fuzzy DEA and fuzzy TOPSIS are applied to a common dataset of logistics service providers. • TOPSIS outperforms DEA in both calculation complexity and sensitivity to number of suppliers. • Output rankings from the two models are found to be less than perfectly correlated. • Utilizing both methods produces a useful pooled shortlist of potential sustainable suppliers. • The results provide a basis for negotiating price and service quality commitments. Abstract This paper presents a comparative analysis of the outcomes achieved when two widely applied methods for supplier selection—the 'technique for order of preference by similarity to ideal solution' (TOPSIS) and 'data envelopment analysis'—are applied to the problem of identifying the most preferred sustainable suppliers. Both fuzzy DEA and fuzzy TOPSIS are applied to a common dataset of logistics service providers in Sweden. The results reveal that TOPSIS outperforms DEA in terms of both calculation complexity and sensitivity to changes in the number of suppliers. However, output rankings from the two models are found to be less than perfectly correlated. The paper concludes that utilizing both methods, as applied to just a small number of evaluation criteria and a relatively low level of detail in the data, produces a useful pooled shortlist of potential sustainable suppliers. This can then form the basis for a second stage application where either of the methods may be applied to a greater number of criteria that are specified to a higher level of detail. Even more critically, the results also have the potential to point to specific aspects for discussion when negotiating price and service quality commitments with potential sustainable suppliers. [ABSTRACT FROM AUTHOR]

Abstract In 2016, Microsoft released the mixed reality (MR) head-mounted display (HMD) HoloLensTM. As augmented reality (AR) devices, the HoloLensTM can enrich the user's perceived environment with virtual information. However, Microsoft does not consider the HoloLensTM as AR device, but as the first MR device, since it has some additional features compared to competing AR devices. Especially to mention is the possibility to interact with virtual objects and vice versa. This paper shall provide an insight about the application potentials of MR in the field of production and logistics. For this purpose, we present the findings of a literature review about the current state of research concerning the application of Microsoft HoloLensTM in the field of production and logistics. Furthermore, we present a small HoloLensTM application, which we have developed to evaluate the capabilities of the device. Several persons tested our application and gave us feedback concerning the utility and usability of the HoloLensTM. We provide an evaluation of the user experiences at the end of the paper. [ABSTRACT FROM AUTHOR]