Showing papers in "Journal of the Operational Research Society in 2016"

The impact of power structure on the retail service supply chain with an O2O mixed channel

Abstract: While the Internet has provided a new means for retailers to reach consumers, it has fundamentally changed the dynamic of competition in the retail service supply chain. The mix of offline and online channels adds a new dimension of competition, and one central issue of this competition is the pricing strategy between the two channels. How to set prices for both online and offline channels? What is the impact of the supply chain power structure on pricing decisions and the performance? This research aims to address these questions by focusing on a retail service supply chain with an online-to-offline (O2O) mixed dual-channel. From the Supplier-Stackelberg, Retailer-Stackelberg, and Nash game theoretical perspectives, we obtain the optimal prices and maximum profits for both the retailer and supplier under different power structures. The analysis result provides important managerial implications, which will be beneficial to retailers to develop proper pricing strategies.

An interval type-2 fuzzy sets-based TODIM method and its application to green supplier selection

Abstract: With the increasing awareness and significant environmental pressures from various stakeholders, companies have realized the significance of selecting green suppliers to their supply chain activities, which involves multiple criteria with uncertainty and the decision makers’ behaviour with irrational. Interval type-2 fuzzy sets (IT2 FSs) have advantages in modelling uncertainty over type-1 fuzzy sets. And TODIM is an useful non-linear prospect model for selecting the irrationally determined alternatives, but the ratings and weights are crisp values. In this paper, we develop the IT2 FSs-based TODIM method to select green supplier. First, we introduce a new distance computing method for IT2 FSs to assist the dominance models to deal with gains (losses) computation. Second, we identify the gains (losses) computing expression through comparing the ranking values of the IT2 FSs evaluations, and obtain the dominance degree of one alternative over others. Third, we use the presented IT2 FSs ranking method using possibility mean and variation coefficient concepts to defuzzify the dominance degree, and obtain the crisp global performance to select the best alternative. Finally, we also apply the proposed IT2 FSs-based TODIM method to green supplier selection for automobile manufacturers.

Multi-criteria decision-making approaches based on distance measures for linguistic hesitant fuzzy sets

Abstract: Linguistic hesitant fuzzy sets (LHFSs), which can be used to both represent decision-makers’ qualitative preferences and reflect their hesitancy and inconsistency, have attracted much attention due...

Inventory and shelf-space optimization for fresh produce with expiration date under freshness-and-stock-dependent demand rate

Abstract: It is well documented that the demand for fresh produce, to a great extent, depends on how fresh it is and an increase in shelf space for displayed stocks may induce more purchase of the produce. However, relatively little attention has been paid to the effect of expiration date despite the fact that produce deteriorates over time and expiration dates are often an important factor in consumers’ purchase decision. In this paper, we propose an economic order quantity model in which we explicitly specify the demand for fresh produce to be a function of its freshness-expiration date and displayed volume. With the demand being freshness-and-stock dependent, it may be profitable to maintain high stock level at the end of the replenishment cycle. Hence, we relax the traditional assumption of zero ending inventory to non-zero ending inventory. Consequently, the objective here is to determine the optimal level of shelf space size, replenishment cycle time, and/or ending inventory level in an effort of maximizing the total annual profit. We found that the total annual profit is strictly pseudo-concave with regard to the three decision variables, which simplifies the search for the global solution to a local optimal. Numerical examples are then presented to highlight the theoretical implications and managerial insights.

Good Laboratory Practice for optimization research

Abstract: Good Laboratory Practice has been a part of non-clinical research for over 40 years. Optimization Research, despite having many papers discussing standards being published over the same period of time, has yet to embrace standards that underpin its research. In this paper we argue the need to adopt standards in optimization research. Building on previous papers, many of which have suggested that the optimization research community should adopt certain standards, we suggest a concrete set of recommendations that the community should adopt. We also discuss how the proposals in this paper could be progressed.

Risk management and coordination in service supply chains : information, logistics and outsourcing

Abstract: A service supply chain, which is a system formed by a network of suppliers, service designers, service providers and other service partners, aims to transfer available scarce resources into services and deliver them to satisfy customer needs. It is a known fact that service supply chain management is playing a more and more important role in modern economies. However, the unique features of service supply chains also create new challenges that call for proper management of the respective operations. In particular, how to coordinate a service supply chain with risk considerations is a critical issue. In this paper, we concisely examine coordination and risk management challenges in service supply chain systems. We also introduce the technical papers featured in the special issue.

Analysis of collaborative savings and cost allocation techniques for the cooperative carrier facility location problem

Abstract: Transport companies may cooperate to increase their efficiency levels by, for example, the exchange of orders or vehicle capacity. In this paper a new approach to horizontal carrier collaboration is presented: the sharing of distribution centres (DCs) with partnering organisations. This problem can be classified as a cooperative facility location problem and formulated as an innovative mixed integer linear programme. To ensure cooperation sustainability, collaborative costs need to be allocated fairly to the different participants. To analyse the benefits of cooperative facility location and the effects of different cost allocation techniques, numerical experiments based on experimental design are carried out on a UK case study. Sharing DCs may lead to significant cost savings up to 21.6%. In contrast to the case of sharing orders or vehicles, there are diseconomies of scale in terms of the number of partners and more collaborative benefit can be expected when partners are unequal in size. Moreover, results indicate that horizontal collaboration at the level of DCs works well with a limited number of partners and can be based on intuitively appealing cost sharing techniques, which may reduce alliance complexity and enforce the strength of mutual partner relationships.

A fuzzy logic-based hybrid estimation of distribution algorithm for distributed permutation flowshop scheduling problems under machine breakdown

Abstract: As the research interest in distributed scheduling is growing, distributed permutation flowshop scheduling problems (DPFSPs) have recently attracted an increasing attention. This paper presents a fuzzy logic-based hybrid estimation of distribution algorithm (FL-HEDA) to address DPFSPs under machine breakdown with makespan criterion. In order to explore more promising search space, FL-HEDA hybridises the probabilistic model of estimation of distribution algorithm with crossover and mutation operators of genetic algorithm to produce new offspring. In the FL-HEDA, a novel fuzzy logic-based adaptive evolution strategy (FL-AES) is adopted to preserve the population diversity by dynamically adjusting the ratio of offspring generated by the probabilistic model. Moreover, a discrete-event simulator that models the production process under machine breakdown is applied to evaluate expected makespan of offspring individuals. The simulation results show the effectiveness of FL-HEDA in solving DPFSPs under machine breakdown.

A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating

Abstract: This paper presents a dynamic logistics model for medical resources allocation that can be used to control an epidemic diffusion. It couples a forecasting mechanism, constructed for the demand of a medicine in the course of such epidemic diffusion, and a logistics planning system to satisfy the forecasted demand and minimize the total cost. The forecasting mechanism is a time discretized version of the Susceptible-Exposed-Infected-Recovered model that is widely employed in predicting the trajectory of an epidemic diffusion. The logistics planning system is formulated as a mixed 0–1 integer programming problem characterizing the decision making at various levels of hospitals, distribution centers, pharmaceutical plants, and the transportation in between them. The model is built as a closed-loop cycle, comprising forecast phase, planning phase, execution phase, and adjustment phase. The parameters of the forecast mechanism are adjusted in reflection of the real data collected in the execution phase by solving a quadratic programming problem. A numerical example is presented to verify efficiency of the model.

Supply chain coordination in quality improvement with reference effects

Abstract: With increasing public attention on product quality, supply chain quality management has been the focus of considerable research attention in recent years. However, only a few published articles ha...

Supplier risk assessment based on trapezoidal intuitionistic fuzzy numbers and ELECTRE TRI-C: a case illustration involving service suppliers

Abstract: Many companies today have embraced the concept of risk management, usually in the form of enterprise risk management or supply chain risk management. Both are based on a holistic view of risks. Hence, risks related to specific functions within a company must be considered more broadly than previously. Risks, however, involve uncertainty, and the less specific the context in which risks are viewed, the more uncertainty will be involved. One particular way to express uncertainty is through trapezoidal intuitionistic fuzzy numbers (TrIFNs). In this paper, risks that are relevant for supplier risk assessments are first collected from the literature. Then it is illustrated how the multi-criteria decision analysis method ELECTRE TRI-C can be used for sorting suppliers into risk categories, when the risks as well as some of the method’s parameters are expressed with TrIFNs. In order to do this, we make use of a small modification of an existing method for converting TrIFNs into crisp values. The approach is illustrated in a case problem based on a company that is looking for service providers (suppliers) of electrical maintenance. The problem involves 20 suppliers that are sorted into three risk categories based on evaluations from 27 criteria. Results from the case study point to two low risk suppliers. A further ad-hoc analysis suggests one of these to be less risky than the other.

A consistency and consensus-based method to group decision making with interval linguistic preference relations

Abstract: Preference relations are a powerful tool to address decision-making problems. In some situations, because of the complexity of decision-making problems and the inherent uncertainty, the decision makers cannot express their preferences by using numerical values. Interval linguistic preference relations, which are more reliable and informative for the decision-makers’ preferences, are a good choice to cope with this issue. Just as with the other types of preference relations, the consistency and consensus analysis is very importance to ensure the reasonable ranking order by using interval linguistic preference relations. Considering this situation, this paper introduces a consistency concept for interval linguistic preference relations. To measure the consistency of interval linguistic preference relations, a consistency measure is defined. Then, a consistency-based programming model is built, by which the consistent linguistic preference relations with respect to each object can be obtained. To cope with the inconsistency case, two models for deriving the adjusted consistent linguistic preference relations are constructed. Then, a consistency-based programming model to estimate the missing values is built. After that, we present a group consensus index and present some of its desirable properties. Furthermore, a group consensus-based model to determine the weights of the decision makers with respect to each object is established. Finally, an approach to group decision making with interval linguistic preference relations is developed, which is based on the consistency and consensus analysis. Meanwhile, the associated numerical examples are offered to illustrate the application of the procedure.

Promoting impulse buying by allocating retail shelf space to grouped product categories

Abstract: This paper addresses a problem where a retailer seeks to optimize store-wide shelf-space allocation in order to maximize the visibility of products to consumers and consequently stimulate impulse buying. We consider a setting where the retailer, because of product affinities or the retailer’s historical practice, has pre-clustered product categories into groups each of which must be assigned to a shelf. On the basis of its location in the store layout, each shelf is partitioned into contiguous shelf segments having different anticipated customer traffic densities. The retailer seeks to assign each group of product categories to a shelf, to determine the relative location of product categories within their assigned shelf, and to specify their allocated total shelf space within given lower/upper bounds. We propose a 0–1 integer programme that takes into account expected customer traffic densities within the store, groups of product categories, their relative profitability, and the desirability to keep certain product groups in the same aisle, with the objective of maximizing the impulse buying profit. The proposed model is grounded in a preprocessing scheme that explores feasible assignments of subsets of product groups to available aisles by iteratively solving an -hard subproblem and is numerically observed to greatly outperform an alternative mixed-integer programming formulation. We demonstrate the usefulness of and the enhanced tractability achieved by the proposed approach using a case study motivated by a grocery store in New England and a variety of simulated problem instances.

Distributed preference relations for multiple attribute decision analysis

Abstract: In this paper, we propose a new pairwise comparison approach called distributed preference relation (DPR) to simultaneously signify preferred, non-preferred, indifferent, and uncertain degrees of one alternative over another on a set of grades, which is more versatile for elicitation of preference information from a decision maker than multiplicative preference relation, fuzzy preference relation (FPR) and intuitionistic FPR. In a DPR matrix on a set of alternatives, each element is a distribution recording the preferred, non-preferred, indifferent, and uncertain degrees of one alternative over another using a set of grades. To facilitate the comparison of alternatives, we define a score matrix based on a DPR matrix using the given score values of the grades. Its additive consistency is constructed, analysed, and compared with the additive consistency of FPRs between alternatives. A method for comparing two interval numbers is then employed to create a possibility matrix from the score matrix, which can generate a ranking order of alternatives with possibility degrees. A problem of evaluating strategic emerging industries is investigated using the approach to demonstrate the application of a DPR matrix to modelling and analysing a multiple attribute decision analysis problem.

A mixed integer formulation and an efficient metaheuristic procedure for the k-Travelling Repairmen Problem

Abstract: In this paper, we study a k-Travelling Repairmen Problem where the objective is to minimize the sum of clients waiting time to receive service. This problem is relevant in applications that involve distribution of humanitarian aid in disaster areas, delivery and collection of perishable products and personnel transportation, where reaching demand points to perform service, fast and fair, is a priority. This paper presents a new mixed integer formulation and a simple and efficient metaheuristic algorithm. The proposed formulation consumes less computational time and allows solving to optimality more than three times larger data instances than the previous formulation published in literature, even outperforming a recently published Branch and Price and Cut algorithm for this problem. The proposed metaheuristic algorithm solved to optimality 386 out of 389 tested instances in a very short computational time. For larger instances, the algorithm was assessed using the best results reported in the literature for the Cumulative Capacitated Vehicle Routing Problem.

Design outsourcing in the fashion supply chain: OEM versus ODM

Abstract: Design innovation is the engine of fashion. Many fashion firms outsource design innovation to their suppliers. Design outsourcing is on the rise in the fashion supply chain, but research in this area lags behind industry practice. In this paper, we examine how design outsourcing affects the supply chain, and we compare supply chain performance under an Original Equipment Manufacturer (OEM) strategy versus an Original Design Manufacturer (ODM) strategy. We evaluate a market size outsourcing model where design enhancement influences market size, and a success probability outsourcing model where design enhancement influences the success probability of innovation. We find that when the supplier trades with the retailer via a wholesale price contract under the ODM strategy, the supplier has no incentive to invest in innovation. In the market size outsourcing model, the design innovation in the centralized supply chain is higher than that under the OEM strategy. However, in the success probability outsourcing model, the success probability of innovation under the OEM strategy is higher than that in the centralized supply chain. Furthermore, we find that a profit sharing contract can achieve supply chain coordination under both OEM and ODM strategies; whereas, revenue sharing and buyback contracts cannot.

Bankruptcy prediction of small and medium enterprises using a flexible binary generalized extreme value model

Abstract: We introduce a binary regression accounting-based model for bankruptcy prediction of small and medium enterprises (SMEs). The main advantage of the model lies in its predictive performance in identifying defaulted SMEs. Another advantage, which is especially relevant for banks, is that the relationship between the accounting characteristics of SMEs and response is not assumed a priori (eg, linear, quadratic or cubic) and can be determined from the data. The proposed approach uses the quantile function of the generalized extreme value distribution as link function as well as smooth functions of accounting characteristics to flexibly model covariate effects. Therefore, the usual assumptions in scoring models of symmetric link function and linear or pre-specified covariate-response relationships are relaxed. Out-of-sample and out-of-time validation on Italian data shows that our proposal outperforms the commonly used (logistic) scoring model for different default horizons.

Efficiency and benchmarking with directional distances: a data driven approach

Abstract: In efficiency analysis the assessment of the performance of Decision-Making Units (DMUs) relays on the selection of the direction along which the distance from the efficient frontier is measured. Directional Distance Functions (DDFs) represent a flexible way to gauge the inefficiency of DMUs. Permitting the selection of a direction towards the efficient frontier is often useful in empirical applications. As a matter of fact, many papers in the literature have proposed specific DDFs suitable for different contexts of application. Nevertheless, the selection of a direction implies the choice of an efficiency target which is imposed to all the analysed DMUs. Moreover, there exist many situations in which there is no a priori economic or managerial rationale to impose a subjective efficiency target. In this paper we propose a data-driven approach to find out an ‘objective’ direction along which to gauge the inefficiency of each DMU. Our approach permits to take into account for the heterogeneity of DMUs and their diverse contexts that may influence their input and/or output mixes. Our method is also a data-driven technique for benchmarking each DMU. We describe how to implement our framework and illustrate its usefulness with simulated and real data sets.

Loss-averse newsvendor problem with supply risk

Abstract: Modeling the manufacturer as a newsvendor, in this paper we study the ordering decisions of a loss-averse newsvendor with supply and demand uncertainties. Using the stylized newsvendor models, we analyse several key issues, including the effect of the newsvendor’s loss aversion, the effect of demand uncertainty, and the effect of supply uncertainty on the decision maker’s optimal decision under the procurement model, in which the decision maker only pays for the actual quantity received. Through our analysis, we find the following facts: the optimal order quantity decreases with respect to the degree of loss-aversion; the supply uncertainty induces the decision maker to order more than that in a deterministic environment; a stochastically larger demand always results in a larger order quantity and a larger expected utility; the optimal expected utility decreases in the demand volatility while the optimal order quantity may increase or decrease. Moreover, with numerical experiments, we demonstrate that the supply risk negatively affects the utility more than the demand risk does.

Cutting and packing problems for irregular objects with continuous rotations: mathematical modelling and non-linear optimization

Abstract: We further improve our methodology for solving irregular packing and cutting problems. We deal with an accurate representation of objects bounded by circular arcs and line segments and allow their continuous rotations and translations within rectangular and circular containers. We formulate a basic irregular placement problem which covers a wide spectrum of packing and cutting problems. We provide an exact non-linear programming (NLP) model of the problem, employing ready-to-use phi-functions. We develop an efficient solution algorithm to search for local optimal solutions for the problem in a reasonable time. The algorithm reduces our problem to a sequence of NLP subproblems and employs optimization procedures to generate starting feasible points and feasible subregions. Our algorithm allows us to considerably reduce the number of inequalities in NLP subproblems. To show the benefits of our methodology we give computational results for a number of new challenger and the best known benchmark instances.

Coordination in a distribution channel with decisions on the nature of incentives and share-dependency on pricing

Abstract: We research the most suitable coordination mechanism for a distribution channel that is composed of one manufacturer and one retailer. Coordination is sought through a Revenue Sharing Contract (RSC...

Forecast-driven model for prepositioning supplies in preparation for a foreseen hurricane

Abstract: In this paper, we present a forecast-driven dynamic model for prepositioning relief items in preparation for a foreseen hurricane. Our model uses forecast advisories issued by the National Hurricane Center (NHC), which are issued every 6 h. Every time a new advisory is issued with updated information, our model determines the amount and location of units to be prepositioned and it also re-prepositions already prepositioned units. The model also determines the best time for starting the prepositioning activities. Our approach uses a combination of Decision Theory and stochastic programming. The outcomes of our model are presented in a way that could be easily understood by humanitarian practitioners who are ultimately the ones who would use and apply our model.

Integrating expert weighting and multi-criteria decision making into eco-efficiency analysis: the case of US manufacturing

Abstract: In this paper, the effect of weighting strategies on sustainability performance assessment is addressed. Eco-efficiency is used as the main metric for sustainability performance evaluation. An integrated input-output life cycle assessment (LCA) and multi criteria decision making (MCDM) approach is employed. The US manufacturing sectors’ LCA results are used in conjunction with the proposed MCDM framework to perform the eco-efficiency evaluation of 276 US manufacturing sectors. Five environmental impact categories are considered as the negative factors, namely: greenhouse gas emissions, energy use, water withdrawal, hazardous waste generation and toxic releases into air and the economic output of each manufacturing sector is considered to be the positive output. To study the overall impact of different weighting strategies; twenty weighting scenarios are designed. Five pairs of weights considered for the overall economic versus environmental impacts along with four specific weighting strategies based on Harvard, SAB, EPP and Equal weighting for each pair. According to the results of the statistical analysis, it is concluded that the weighing strategies applied to the overall environmental impacts and economic outputs cause statistically significant differences in the eco-efficiency scores.

Virtual enterprise partner selection integrating LINMAP and TOPSIS

Abstract: Virtual enterprise (VE) has become an ever-increasing trend in today’s highly competitive markets. A more scientific decision-making process for selecting partner is very important during the formation phase of VE. Partner selection is formulated as a type of fuzzy hybrid multi-criteria group decision-making problems with fuzzy truth degrees of alternatives’ comparisons represented as trapezoidal fuzzy numbers (TrFNs). Integrating Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP), we use the relative closeness degrees to define fuzzy consistency and inconsistency indices. The decision makers’ weight vector is derived by using the relative entropy. Criteria weights are estimated through constructing a new fuzzy linear programming model with TrFNs, which is solved by the developed fast and efficient method. Collective ranking matrix of alternatives is generated through constructing multi-objective assignment model. Example analysis demonstrates the effectiveness of the proposed method.

Predicting time-to-churn of prepaid mobile telephone customers using social network analysis

Abstract: Mobile phone carriers in a saturated market must focus on customer retention to maintain profitability. This study investigates the incorporation of social network information into churn prediction models to improve accuracy, timeliness, and profitability. Traditional models are built using customer attributes, however these data are often incomplete for prepaid customers. Alternatively, call record graphs that are current and complete for all customers can be analysed. A procedure was developed to build the call graph and extract relevant features from it to be used in classification models. The scalability and applicability of this technique are demonstrated on a telecommunications data set containing 1.4 million customers and over 30 million calls each month. The models are evaluated based on ROC plots, lift curves, and expected profitability. The results show how using network features can improve performance over local features while retaining high interpretability and usability.

Optimal service contract under cost information symmetry/asymmetry

Abstract: Service outsourcing has become a hot topic in both industry and academy. This paper studies the contract design problems for a service seller who consigns the service to a vendor. The vendor’s service cost parameter may or may not completely be known by the seller, which constitutes the cases of information symmetry or asymmetry. In both cases, the optimal contracts are developed to maximize the seller’s expected profit, with the consideration of contractible and non-contractible service qualities. The properties of the contract parameters are explored, along with the analysis of information rent and value of cost information. Moreover, we find that non-contractible service quality is not an issue for the service seller under cost information symmetry since a revenue-sharing type of contract can guarantee the seller’s profit. However, this result does not hold under cost information asymmetry and thus non-contractibility of the service quality indeed costs the seller.

Determining common weights in data envelopment analysis based on the satisfaction degree

Abstract: The traditional data envelopment analysis model allows the decision-making units (DMUs) to evaluate their maximum efficiency values using their most favourable weights. This kind of evaluation with...

An ILS-biased randomization algorithm for the two-dimensional loading HFVRP with sequential loading and items rotation

Abstract: This paper discusses the Two-dimensional Loading Vehicle Routing Problem with Heterogeneous Fleet, Sequential Loading, and Item Rotation (2L-HFVRP-SR). Despite the fact that the 2L-HFVRP-SR can be found in many real-life situations related to the transportation of voluminous items, where heterogeneity of fleets, two-dimensional packing restrictions, sequential loading, and items rotation have to be considered, this rich version of vehicle routing-and-packing problem has been rarely analysed in the literature. Accordingly, this paper contributes to filling the gap by presenting a relatively simple-to-implement algorithm which is able to provide state-of-the-art solutions for such a complex problem in relatively short computational times. The proposed algorithm integrates inside an Iterated Local Search framework, biased-randomized versions of both vehicle routing and packing heuristics. The efficiency of the proposed algorithm is validated throughout an extensive set of computational tests.

Berth allocation in container terminals that service feeder ships and deep-sea vessels

Abstract: This paper treats a berth allocation problem (BAP) in dedicated container terminals where feeder ships and container vessels are jointly served. When assigning quay space and a service time to each calling ship particular focus is put on the container exchange between feeder ships and mother vessels, so that the weighted number of containers delivered by feeder missing their intended mother vessel (and vice versa) does not exceed a given upper bound. The resulting BAP is formalized, complexity proofs are provided, and suited optimization procedures are presented and tested.

Bi-criterion single-machine scheduling and due-window assignment with common flow allowances and resource-dependent processing times

Abstract: This paper addresses single-machine scheduling and due-window assignment with common flow allowances and resource-dependent processing times. Due-window assignment with common flow allowances means...