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This paper proposes a hybrid algorithm to tackle a real-world problem arising in the context of pulp and paper production. This situation is modelled as a production problem where one has to decide which wood will be used by each available processing unit (wood cooker) in order to minimize the variance of wood densities within each cooker for each period of the planning horizon. The proposed hybrid algorithm is built around two distinct phases. The first phase uses two interacting heuristic methods to identify a promising reduced search space, which is then thoroughly explored in the second phase. This hybrid algorithm produces high-quality solutions in reasonable computation times, especially for the largest test instances. Extensive computational experiments demonstrated the robustness and efficiency of the method.

Paper machines are very complex production systems, but their scope is simple: they consume materials and resources, called factors, to produce paper, which in turn can be described by its characteristics. In this paper, a decision support system is developed in cooperation with an industrial partner to help them with operational decision making when tuning a paper machine. The decision support system was developed in two phases. Firstly, the knowledge of experts is collected and stored in the form of a fuzzy ontology. Secondly, this knowledge is made usable so that a user of the decision support system can specify what characteristics of the produced paper to increase or to decrease and be returned with a recommendation on what factors to change. In this paper, we will work out the optimization problems on which the system is based. Additionally to a basic goal programming model, two extensions are explored, accounting for uncertainty and non-linearity, respectively.

Many policy problems are complex in the sense that natural, technological, social and human elements interact. Problem exploration and structuring are essential as a basis for deliberate and focused approaches towards problem resolution. The results of problem exploration efforts can be laid down in the form of a policy issue paper. We have developed a systemic, stepwise approach, which has been elaborated and taught for over a decade to hundreds of students. This seven-step approach centers on the construction of a system diagram as a means to provide structure to the conceptualisation of a complex problem situation. The approach is based on a conscious combination of existing relatively straightforward analytical methods including objectives hierarchy, means-ends analysis, causal diagramming, stakeholder analysis, and contextual scenarios. The obtained insights are then summed up in a policy issue paper, which is the basis for further planning and research.

In the conclusion to his paper on statistical modelling in management science Mingers (2006) summarizes criticisms of econometric forecasting and suggests that ‘we must accept these inevitable limi...

In his paper, Georgiou1 reviews the various uses of the term emergent property and summarizes the meaning of emergent property as understood in systems theory. He then notes an agenda set by Checkl...

(2001). JORS part special issue OR42 papers: an editorial overview. Journal of the Operational Research Society: Vol. 52, Part Special Issue: OR42 Papers, pp. 855-855.

Why should anyone spend ?80 on this book? This is not intended as a criticism of either the Dutch or the German Operational Research Societies, of whose 1993 conference these proceedings are a permanent record. No; it is a comment on the academic book publishing industry, which chooses to make a compilation of the papers presented at a conference, sticks a (paperback) cover on them and charges a fancy price to libraries that feel obliged to buy the result. For my money, I should far rather take out a subscription to Interfaces or Operations Research and receive a stream of refereed papers that covers much the same material. Unfortunately, the European Journal of Operational Research has priced itself out of the personal subscription market, so I cannot recommend the natural home of the best of these papers as an alternative to buying this volume. Having put this volume in context, what more is there to say? Well I think that it actually shows Operational Research to be doing rather better on the Continent than it is in the UK. By that I mean that there is more 'real OR' being done, with real clients paying real money (or spending significant amounts of time with academics) to have their problems tackled. True, there is the same hefty bias among contributors to this volume towards academia as in the UK, but one is not left with the impression that OR is a subject to be practised by consenting adults in the privacy of their own universities. Even so, in his plenary lecture 'The Practice of OR', Gerrit Timmer quotes Alexander Rinnooy Kan

Barber Ellis Fine Papers (BEFP) is a Canadian distributor of about 10,000 SKUs to several thousand small or medium-sized firms in the printing and graphic arts industries. A considerable increase in sales is anticipated over the next few years, requiring BEFP to make some important policy decisions in inventory, warehousing and transportation. Two methodologies were employed in our analysis. First, a spreadsheet model was used to simulate several particular inventory/distribution alternatives, e.g. the present decentralized system and a system based on a national distribution centre. Secondly, linear programming was used to obtain the best system alternative, consistent with constraints on capacities, demands, etc. Details of the methods, the results and conclusions are given. Relative merits of simulation and optimization models for this type of inventory/distribution problem are noted, and suggestions are made for further research.

(1979). A Note on the Paper: An Inventory Model with Finite Horizon and Price Changes. Journal of the Operational Research Society: Vol. 30, No. 9, pp. 839-840.

(1977). A Supplement to a Paper on Queueing Approximations. Journal of the Operational Research Society: Vol. 28, No. 3, pp. 596-597.

The use of forest fuel is increasing at heating plants in Sweden. Heating plants provide energy in the form of hot water for heating houses and apartments in local municipalities. Forest fuel are products obtained from harvesting in forests that cannot be used for further processing at sawmills and pulp and paper mills. Examples of such products are tree branches, tree tops and low quality logs. The optimization of the supply chain for round-wood (logs to sawmills, pulp and paper mills) and for forest fuel is similar but involves two main differences. First, forest fuel has to be converted into chips before delivery to the customer, and second, the demand for forest fuel varies over the year due to the temperature. To balance the chipping and transportation capacities over time, it is important to manage inventory levels at terminals. The optimization model developed provides decision support for questions regarding the choice of technology for chipping, where to perform the chipping operations, and the allocation of different assortments to heating plants. The system has been tested on a large case study from a Swedish forest energy company. The results show large savings and that the system is very useful for both planning and business development.

A large number of studies have applied simulation to a multitude of issues relating to healthcare. These studies have been published in a number of unrelated publishing outlets, which may hamper the widespread reference and use of such resources. In this paper, we analyse existing research in healthcare simulation in order to categorise and synthesise it in a meaningful manner. Hence, the aim of this paper is to conduct a review of the literature pertaining to simulation research within healthcare in order to ascertain its current development. A review of approximately 250 high-quality journal papers published between 1970 and 2007 on healthcare-related simulation research was conducted. The results present a classification of the healthcare publications according to the simulation techniques they employ; the impact of published literature in healthcare simulation; a report on demonstration and implementation of the studies’ results; the sources of funding; and the software used. Healthcare planners and researchers will benefit from this study by having ready access to an indicative article collection of simulation techniques applied to healthcare problems that are clustered under meaningful headings. This study facilitates the understanding of the potential of different simulation techniques in solving diverse healthcare problems.

This paper provides a comprehensive review of the applications of data science techniques and methodologies in productivity. The paper is structured as a combination of a bibliometric analysis and ...

Limited attention has been paid to assessing the generality performance of hyper-heuristics. The performance of hyper-heuristics has been predominately assessed in terms of optimality which is not ideal as the aim of hyper-heuristics is not to be competitive with state of the art approaches but rather to raise the level of generality, i.e. the ability of a technique to produce good results for different problem instances or problems rather than the best results for some instances and poor results for others. Furthermore from existing literature in this area it is evident that different hyper-heuristics aim to achieve different levels of generality and need to be assessed as such. To cater for this the paper firstly presents a new taxonomy of four different levels of generality that can be attained by a hyper-heuristic based on a survey of the literature. The paper then proposes a performance measure to assess the performance of different types of hyper-heuristics at the four levels of generality in terms of generality rather than optimality. Three case studies from the literature are used to demonstrate the application of the generality performance measure. The paper concludes by examining how the generality measure can be combined with measures of other performance criteria, such as optimality, to assess hyper-heuristic performance on more than one criterion.

This paper presents a price discrimination model for a manufacturer who acts in two different markets. In order to have a fair price discrimination model and compare monopoly and competitive markets, it is assumed that there is no competitor in the first market (monopoly market) and there is a strong competitor in the other market (competitive market). The manufacturer objective is to maximize the total benefit in both markets. The decision variables are selling price, lot size, marketing expenditure, customer service cost, flexibility and reliability of production process, set up costs and quality of products. The proposed model in this paper is a signomial geometric programming problem which is difficult to solve and find the globally optimal solution. So, this signomial model is converted to a posynomial geometric type and using an iterative method, the globally optimal solution is found. To illustrate the capability of the proposed model, a numerical example is solved and the sensitivity analysis is implemented under different conditions.

This paper introduces a novel method for asset and option trading in a binomial scenario. This method uses nonparametric predictive inference (NPI), a statistical methodology within im- precise probability theory. Instead of inducing a single probability distribution from the existing observations, the imprecise method used here induces a set of probability distributions. Based on the induced imprecise probability, one could form a set of conservative trading strategies for assets and options. By integrating NPI imprecise probability and expectation with the classical nancial binomial tree model, two rational decision routes for asset trading and for European option trading are suggested. The performances of these trading routes are investigated by com- puter simulations. The simulation results indicate that the NPI based trading routes presented in this paper have good predictive properties.

Ozkan, Omer/0000-0002-3839-2754; Ermis, Murat/0000-0002-4524-6800; Bekmezci, Ilker/0000-0001-7299-9448 WOS:000530954200008 Reliable communication network design (RCND) is a well-known optimisation problem to produce a network with maximum reliability. This paper addresses the minimum cost communication network design problem under the all-terminal reliability constraint. Due to the NP-hard nature of RCND, several different metaheuristic algorithms have been widely applied to solve this problem. The aim of this paper is to propose two new hybrid metaheuristic algorithms, namely, GABB and SABB, by integrating either a Genetic Algorithm (GA) with the Branch and Bound method (B&B) or Simulated Annealing (SA) with B&B. The GABB and SABB algorithms have the advantages of finding higher performance solutions produced from the GA or SA, along with the ability to repair infeasible solutions or improve solution quality by integrating the B&B method. To investigate the effectiveness of the proposed algorithms, extensive comparisons with individual application of the GA and SA (the basic forms of GABB and SABB), two different hybrid algorithms (GABB and SABB) and other two approaches (ACO_SA and STH) that give the best results in the literature for the design problems are carried out in a three-stage experimental study (ie, small-, medium-, and large-sized networks). The computational results show that hybridisation of metaheuristics with the B&B method is an effective approach to designing reliable networks and finding better solutions for existing problems in the literature.

This paper emphasises the sensitivity of the data envelopment analysis (DEA) efficiency estimators to sampling variations of the production frontier and dimensionality of the production set. It has been proven that DEA yields asymptotic unbiased estimates. A DEA (smoothed) bootstrap method is widely being applied to address the inaccuracy of DEA estimators. The combination of DEA and a modified bootstrap expression enhances the statistical properties of DEA estimators without overcoming the inherent limitations of each of the two methods. This paper provides a non-resampling multi-parametric method to deal with the sensitivity of DEA estimators. The new method is applied to scaled samples, and the bias-corrected efficiency estimators are compared against their population counterparts. A comparative analysis among the standard bootstrap, the smoothed bootstrap, and the new method shows that the new method’s estimations provide a better fit to the population than the estimations of the standard and ...

Serious information security breaches have caused firms to suffer from customer churns directly or indirectly. To prevent customer churns, firms usually enhance their security protection through two measures, i.e. security investment and security information sharing. Prior studies seldom consider security environment and business environment simultaneously when making a firm’s optimal security decisions. Using game theory, this paper purports to demonstrate that a firm’s security decisions under a competitive environment differ significantly from those under an integrated environment. Moreover, distortions may surface if firms do not cooperate on security practices. Thus, this paper further analyses the measures that a social planner such as the government or industry association controls firms’ security decisions, and results show that these measures may not always be effective. Instead, social planners are recommended to enhance or attenuate the controlling level of the two security decisions ba...

Newsvendor problems, which have attracted the attention of researchers since 1950s, have wide applications in various industries. There have been many extensions to the standard single-period newsvendor problem. In this paper, we consider the single-period, single-item and single-stage newsvendor problem under random end-of-season demand and develop a model to determine the optimal order quantity and expected profit. We prove that the optimal order quantity and expected profit thus obtained are lower than their respective values obtained from the standard newsvendor formulation. We also provide numerical examples and perform sensitivity analyses to compute the extent of deviations of the ‘true’ optimal solutions from the newsvendor solutions. We observe that the deviations are most sensitive to the ratio of the means of the demand distributions. The deviations are also found sensitive to the contribution margin, salvage price, coefficients of variation of the demand distributions and correlation between seasonal and end-of-season demands. We provide broad guidelines for managers as to when the model developed in this paper should be used and when the standard newsvendor formulation would suffice to determine the order quantity.

The essence of data plays a critical role in decision making in supply chain management (SCM). When data embedded in supply chains (SCs) are fuzzy, the associated equilibrium and performance measures also become fuzzy. This paper investigates the effects of fuzzy data on decision making in a two-echelon SC with a supplier and duopolistic retailers playing a Stackelberg strategic game in both intra- and inter-echelons. In contrast to existing approaches, this paper devises an analysis method to provide a likely interval of the fuzzy maximal profit with a known possibility level (degree of certainty) rather than a singleton (crisp value). The idea is based on the extension principle to reformulate the two-level optimization problem as a pair of parametric quadratic programs in order to calculate the lower and upper bounds of the leader’s fuzzy maximal profit at each possibility level of the obtained information. The analytic results indicate that the higher the degree of uncertainty, the smaller (larger) the lower (upper) bound of the maximum profit of each SC member. Moreover, the main results obtained from eight scenarios show that when the degree of demand diversity between the two retailers is significantly high, the Stackelberg leader is most likely to obtain lower profit and the marginal contribution of the primary demand to the total profit of the duopolistic retailers will exceed that of the powerful supplier’s maximum profit.

A simulation study consists of several stages: problem formulation, model implementation, verification and validation, experimentation and output data analysis. The application of multiple techniques in the model implementation stage is referred to as hybrid simulation, which we distinguish in this paper from a hybrid M&S study, the latter referring to studies that apply methods and techniques from disciplines like Operations Research (OR), Systems Engineering and Computer Science to one or more stages of a simulation study. Our paper focuses on the contribution of soft OR methods in the problem formulation stage of a simulation study (and by extension a hybrid M&S study). Soft Systems Methodology (SSM) has, arguably, been the most widely used qualitative approach for eliciting system requirements. In this paper, we present Qualitative System Dynamics (QSD), a soft systems method, as having potential use in the problem formulation stage of a healthcare M&S study. The contribution of this paper is thus twofold: (1) a review of the literature in SSM for healthcare operations management and (2) an examination of QSD as an additional soft OR method, complementing (rather than supplanting) existing approaches, which can further aid the understanding of the system in the problem formulation/conceptual modelling stage of a hybrid M&S study.

The Dependency Diagram of a Linear Programme (LP) shows how the successive inequalities of an LP depend on former inequalities, when variables are projected out by Fourier- Motzkin Elimination. This is explained in a paper referenced below. The paper, given here, extends the results to the Mixed Integer case (MILP). It is shown how projection of a MILP leads to a finite disjunction of polytopes. This is expressed as a set of inequalities (mirroring those in the LP case) augmented by correction terms with finite domains which are subject to linear congruences.