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 Annals of Operations Research   [SJR: 1.186]   [H-I: 78]   [10 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1572-9338 - ISSN (Online) 0254-5330    Published by Springer-Verlag  [2354 journals]
• The Shapley value in the Knaster gain game
• Authors: Federica Briata; Andrea Dall’Aglio; Marco Dall’Aglio; Vito Fragnelli
Pages: 1 - 19
Abstract: In Briata et al. (AUCO Czech Econ Rev 6:199–208, 2012), the authors introduce a cooperative game with transferable utility for allocating the gain of a collusion among completely risk-averse agents involved in the fair division procedure introduced by Knaster (Ann Soc Pol Math 19:228–230, 1946). In this paper we analyze the Shapley value (Shapley, in: Kuhn, Tucker (eds) Contributions to the theory of games II (Annals of Mathematics Studies 28), Princeton University Press, Princeton, 1953) of the game and propose its use as a measure of the players’ attitude towards collusion. Furthermore, we relate the sign of the Shapley value with the ranking order of the players’ evaluation, and show that some players in a given ranking will always deter collusion. Finally, we characterize the coalitions that maximize the gain from collusion, and suggest an ad-hoc coalition formation mechanism.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2651-8
Issue No: Vol. 259, No. 1-2 (2017)

• The multi-stripe travelling salesman problem
• Authors: Eranda Çela; Vladimir G. Deineko; Gerhard J. Woeginger
Pages: 21 - 34
Abstract: In the classical Travelling Salesman Problem (TSP), the objective function sums the costs for travelling from one city to the next city along the tour. In the q-stripe TSP with $$q\ge 1$$ , the objective function sums the costs for travelling from one city to each of the next q cities in the tour. The resulting q-stripe TSP generalizes the TSP and forms a special case of the quadratic assignment problem. We analyze the computational complexity of the q-stripe TSP for various classes of specially structured distance matrices. We derive NP-hardness results as well as polynomially solvable cases. One of our main results generalizes a well-known theorem of Kalmanson from the classical TSP to the q-stripe TSP.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2513-4
Issue No: Vol. 259, No. 1-2 (2017)

• Pre-positioning of relief inventories for non-profit organizations: a
newsvendor approach
• Authors: Jingxian Chen; Liang Liang; Dong-Qing Yao
Pages: 35 - 63
Abstract: Developing an efficient policy to determine the inventory a non-profit organization (NPO) should stockpile to respond to potential disasters plays a vital role in humanitarian relief. Incorporating social donation and emergency spot purchasing, this paper develops a (generalized) two-stage delivery process model to characterize relief materials’ delivery after a disaster. We propose an analytical model that aims to minimize the total costs when all demands incurred by an unexpected disaster need to be fully satisfied. Moreover, we determine that the optimal solution uniquely exists and characterize the effects of key parameters. Last, this paper also develops a risk-sharing scheme, in which the NPO and the supplier jointly stockpile relief materials. Under some mild conditions, we show that implementing the scheme could increase the storage quantity and decrease the total costs simultaneously. Several numerical examples are employed to validate the model, as well as the value of the proposed risk-sharing scheme.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2521-4
Issue No: Vol. 259, No. 1-2 (2017)

• A flexible elicitation procedure for additive model scale constants
• Authors: Adiel T. de Almeida-Filho; Adiel T. de Almeida; Ana Paula C. S. Costa
Pages: 65 - 83
Abstract: This paper contributes to the process of eliciting additive model scale constants in order to support choice problems, thereby reducing the effort a decision maker (DM) needs to make since partial information with regard to DM preferences can be used. Procedures related to eliciting weights without a tradeoff interpretation of weights are justified based on assumptions that DM is not able to specify fixed weight values or if DM is able to do so, this would not be reliable information. As long as partial information is provided, the flexible elicitation procedure performs dominance tests based on a linear programming problem to explore the DM’s preferences as a vector space which is built using the DM’s partial information. To provide evidence of the satisfactory performance of the flexible elicitation procedure, an empirical test is presented with results that indicate that this procedure requires less effort from DMs.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2519-y
Issue No: Vol. 259, No. 1-2 (2017)

• An applicable method for modifying over-allocated multi-mode resource
constraint schedules in the presence of preemptive resources
• Authors: Aidin Delgoshaei; Timon Rabczuk; Ahad Ali; Mohd Khairol Anuar Ariffin
Pages: 85 - 117
Abstract: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resources over-allocating are frequently seen after scheduling of a project in practice which causes the schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this research a new method is developed for modifying over-allocated schedules in multi-mode resource constrained project scheduling problems with positive cash flows (MRCPSP-PDC). The aim is maximizing net present value of the MRCPSPs (or logically minimizing negative cash flows). The proposed method is designed to consider all types of activity precedence including Finish to Start, Start to Start, Finish to Finish and Start to Finish and also lags between activities. It can also be used alone or as a macro in Microsoft Office Project $$^{\textregistered }$$ Software to modify resource over-allocated days after scheduling a project. In this research progress payment method and preemptive resources are considered. The proposed approach maximizes NPV by scheduling activities through the resource calendar respecting to the available level of pre-emptive resources and activity numbers. To examine the performance of the proposed method a number of experiments that is derived from the literature are solved. The results are then compared with the state where resource constraints are relaxed and also Simulated Annealing algorithm. The outcomes show that the proposed algorithm can provide modified schedules with no over-allocated days for experiment with 1000 activities and 100 preemptive resources in a few seconds. The method is then applied for scheduling a manufacturing project in practice.
PubDate: 2017-12-01
DOI: 10.1007/s10479-016-2336-8
Issue No: Vol. 259, No. 1-2 (2017)

• Performance evaluation of the Taiwan railway administration
• Authors: Bo Hsiao; LihChyun Shu; Ming-Miin Yu; Li-Kang Shen; Ding-Jiun Wang
Pages: 119 - 156
Abstract: This study aims to investigate the effects of centralized allocation and optimization of railway resources on overall operational efficiency of the railway industry. Its results are intended to help Taiwan railway industry in resource allocation and reduction of organization resistance caused by resource deployment in Taiwan. For this purpose, this study proposes and divides resource reallocation into long-, middle-, and short-term plans, with three resource adjustment programs. These programs consider different geographical ranges and resource conditions of personnel and equipment in resource allocation by using a two-phase centralized data envelopment analysis. Conducted in 2011, the Taiwan railway data analysis indicated that high overall output that was attributed to efficient allocation of resources induced large-scale organizational changes and adjustments (such as staff reduction) in the railway industry. These changes resulted in widespread organization resistance. Nonetheless, this process enabled the railway industry in Taiwan to achieve balance between output and organization resistance under different environments efficiently.
PubDate: 2017-12-01
DOI: 10.1007/s10479-016-2190-8
Issue No: Vol. 259, No. 1-2 (2017)

• Partially concurrent open shop scheduling with integral preemptions
• Authors: Hagai Ilani; Elad Shufan; Tal Grinshpoun
Pages: 157 - 171
Abstract: Partially-concurrent open shop scheduling (PCOSS) was recently introduced as a common generalization of the well-known open shop scheduling model and the concurrent open shop scheduling model. PCOSS was shown to be NP-hard even when there is only one machine and all operations have unit processing time. In the present paper we study PCOSS problems with integral processing times that allow preemptions at integral time points. A special and simple subclass of the problems at focus is that of unit processing times, which is considered separately. For these two cases a schedule is related to the colouring of a graph called the conflict graph, which represents the operations that cannot be performed concurrently. This enables us to extract insights and solutions from the well-studied field of graph colouring and apply them to the recently introduced PCOSS model. We then focus on two special cases of the problem—the case where the conflict graph is perfect, and the case of uniform PCOSS, in which all the jobs, including their conflicts, are identical. The development of the PCOSS model was motivated from a real-life timetabling project of assigning technicians to a fleet of airplanes. The latter case of uniform PCOSS correlates to instances in which the fleet of airplanes is homogeneous.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2503-6
Issue No: Vol. 259, No. 1-2 (2017)

• Using managerial revenue and cost estimates to value early stage real
option investments
• Authors: Sebastian Jaimungal; Yuri Lawryshyn
Pages: 173 - 190
Abstract: Real options analysis is widely recognized as a superior method for valuing projects with managerial flexibilities. Yet, its adoption remains limited due to varied difficulties in its implementation. In this work, a real options approach that utilizes managerial cash-flow estimates to value early stage project investments is proposed. Our model is based on the assumption that managers can provide pessimistic, likely and optimistic sales and gross margin percent estimates. A market sector indicator is introduced, which is assumed to be correlated to a tradeable market index, which drives the project’s sales estimates. Another indicator, assumed partially correlated to the sales indicator drives the gross margin percent estimates. In this way a cash-flow process can be modelled that is partially correlated to a traded market index. This provides the mechanism for valuing real options of the cash-flow in a financially consistent manner. The method requires minimal subjective input of model parameters and is very easy to implement, based on simple managerial estimates.
PubDate: 2017-12-01
DOI: 10.1007/s10479-016-2344-8
Issue No: Vol. 259, No. 1-2 (2017)

• Novel formulations and VNS-based heuristics for single and multiple
allocation p -hub maximal covering problems
• Authors: Olivera Janković; Stefan Mišković; Zorica Stanimirović; Raca Todosijević
Pages: 191 - 216
Abstract: This paper deals with uncapacitated single and multiple allocation p-hub maximal covering problems (USApHMCP and UMApHMCP) with binary and partial covering criteria. We present new mixed-integer programming formulations of the considered problems, which are valid for both binary and partial coverage cases. The efficiency of the proposed formulations is evaluated through computational experiments on smaller-size instances, and compared with the state-of-the art models from the literature. The obtained results indicate that the new UMApHMCP formulation outperforms the existing one for both coverage criteria in the sense of solutions’ quality and running times. In order to solve instances of larger problem dimension, we develop two heuristic methods based on variable neighborhood search: general VNS (GVNS) for USApHMCP and basic VNS (BVNS) for UMApHMCP. The proposed GVNS and BVNS involve the same shaking procedure in order to hopefully escape local minima traps, while local search phases in GVNS and BVNS use different neighborhood structures in accordance with applied allocation schemes. Computational experiments conducted on smaller-size instances showed that both GVNS and BVNS almost instantly reach all known optimal solutions. In addition, the proposed GVNS and BVNS showed to be very efficient when solving large and large-scale hub instances with up to 1000 nodes, which were not previously considered as test instances for the considered problems. Both GVNS and BVNS provided best solutions on challenging USApHMCP and UMApHMCP instances for both coverage cases in short running times, which indicates their potential to be applied to similar problems.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2508-1
Issue No: Vol. 259, No. 1-2 (2017)

• Quantifying sustainable control of inventory systems with non-linear
backorder costs
• Authors: Lina Johansson; Fredrik Olsson
Pages: 217 - 239
Abstract: Traditionally, when optimizing base-stock levels in spare parts inventory systems, it is common to base the decisions either on a linear shortage cost or on a certain target fill rate. However, in many practical settings the shortage cost is a non-linear function of the customer waiting time. In particular, there may exist contracts between the spare parts provider and the customer, where the provider is obliged to pay a fixed penalty fee if the spare part is not delivered within a certain time window. We consider a two-echelon inventory system with one central warehouse and multiple local sites. Focusing on spare parts products, we assume continuous review base stock policies. We first consider a fixed backorder cost whenever a customer’s time in backorder exceeds a prescribed time limit, second a general non-linear backorder cost as a function of the customer waiting time, and third a time window service constraint. We show from a sustainability perspective how our model may be used for evaluating the expected $$\hbox {CO}_2$$ emissions associated with not satisfying the customer demands on time. Finally, we generalize some known inventory models by deriving exact closed form expressions of inventory level distributions.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2542-z
Issue No: Vol. 259, No. 1-2 (2017)

• An aggressive game cross-efficiency evaluation in data envelopment
analysis
• Authors: Wenli Liu; Ying-Ming Wang; Shulong Lv
Pages: 241 - 258
Abstract: Cross-efficiency evaluation is an effective method for ranking decision making units (DMUs) in data envelopment analysis, which is performed with peer-evaluation and self-evaluation. From different points of view, various cross-efficiency evaluations have been proposed with different secondary goals. Yet they usually lead to different average cross-efficiencies and different rankings. In this paper, we develop a concept of the aggressive game cross-efficiency, and propose an aggressive secondary model to minimize the cross-efficiencies of other DMUs under the constraints that the aggressive game cross-efficiency of the evaluated DMU is guaranteed. To achieve the aggressive game cross-efficiency, we develop an iterative algorithm. Mathematically, it is proved that all conventional average cross-efficiencies are sure to converge to the same aggressive game cross-efficiency by the iterative algorithm. Finally, numerical examples are presented to show the effectiveness of our approach in evaluating and ranking DMUs.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2524-1
Issue No: Vol. 259, No. 1-2 (2017)

• Robust multicriteria risk-averse stochastic programming models
• Authors: Xiao Liu; Simge Küçükyavuz; Nilay Noyan
Pages: 259 - 294
Abstract: In this paper, we study risk-averse models for multicriteria optimization problems under uncertainty. We use a weighted sum-based scalarization and take a robust approach by considering a set of scalarization vectors to address the ambiguity and inconsistency in the relative weights of each criterion. We model the risk aversion of the decision makers via the concept of multivariate conditional value-at-risk (CVaR). First, we introduce a model that optimizes the worst-case multivariate CVaR and show that its optimal solution lies on a particular type of stochastic efficient frontier. To solve this model, we develop a finitely convergent delayed cut generation algorithm for finite probability spaces. We also show that the proposed model can be reformulated as a compact linear program under certain assumptions. In addition, for the cut generation problem, which is in general a mixed-integer program, we give a stronger formulation than the existing ones for the equiprobable case. Next, we observe that similar polyhedral enhancements are also useful for a related class of multivariate CVaR-constrained optimization problems that has attracted attention recently. In our computational study, we use a budget allocation application to benchmark our proposed maximin type risk-averse model against its risk-neutral counterpart and a related multivariate CVaR-constrained model. Finally, we illustrate the effectiveness of the proposed solution methods for both classes of models.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2526-z
Issue No: Vol. 259, No. 1-2 (2017)

• Typology and literature review for dial-a-ride problems
• Authors: Yves Molenbruch; Kris Braekers; An Caris
Pages: 295 - 325
Abstract: Dial-a-ride problems consist of designing vehicle routes and time schedules in a system of demand-dependent, collective people transportation. In the standard problem, operational costs are minimized, subject to full demand satisfaction and service level requirements. However, to enhance the practical applicability of solution methods, authors increasingly focus on problem variants that adopt additional real-life characteristics. First, this work introduces an up-to-date classification that distinguishes multiple categories of real-life characteristics. Second, the wide range of solution methods proposed in the literature is reviewed in a structured manner. Although the existing literature is reviewed exhaustively, specific attention is devoted to recent developments. Third, an extensive overview table provides full details on all problem characteristics and solution methods applied in each paper discussed. Fourth, lacunae in research conducted to date and opportunities for future work are identified.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2525-0
Issue No: Vol. 259, No. 1-2 (2017)

• An ILP-based local search procedure for the VRP with pickups and
deliveries
• Authors: Agustín Montero; Juan José Miranda-Bront; Isabel Méndez-Díaz
Pages: 327 - 350
Abstract: In this paper we address the Vehicle Routing Problem with Pickups and Deliveries (VRPPD), an extension of the classical Vehicle Routing Problem (VRP) where we consider precedences among customers, and develop an Integer Linear Programming (ILP) based local search procedure. We consider the capacitated one-to-one variant, where a particular precedence must be satisfied between pairs of origin-destination customers. We extend the scheme proposed in De Franceschi et al. (Math Program 105(2–3):471–499, 2006) for the Distance-Constrained Capacitated VRP, which has been successfully applied to other variants of the VRP. Starting from an initial feasible solution, this scheme follows the destroy/repair paradigm where a set of vertices is removed from the routes and reinserted by solving heuristically an associated ILP formulation with an exponential number of variables, named Reallocation Model. In this research, we propose two formulations for the Reallocation Model when considering pickup and delivery constraints and compare their behavior within the framework in terms of the trade off between the quality of the solutions obtained and the computational effort required. Based on the computational experience, the proposed scheme shows good potential to be applied in practice to this kind of problems and is a good starting point to consider more complex versions of the VRPPD.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2520-5
Issue No: Vol. 259, No. 1-2 (2017)

• A new multi-component DEA approach using common set of weights methodology
and imprecise data: an application to public sector banks in India with
undesirable and shared resources
Pages: 351 - 388
Abstract: Owing to the importance of internal structure of decision making units (DMUs) and data uncertainties in real situations, the present paper focuses on multi-component data envelopment analysis (MC-DEA) approach with imprecise data. The undesirable outputs and shared resources are also incorporated in the production process of multi-component DMUs to validate real problems. The interval efficiencies of DMUs and their components in MC-DEA are often challenging with imprecise data. In many practical situations, different set of weights may be resulted into valid efficiency intervals for DMUs but invalid interval efficiencies for their components. Therefore, the present study proposes a new common set of weights methodology, based on interval arithmetic and unified production frontier, to determine unique weights for measuring these interval efficiencies. It is a two-level mathematical programming approach that preserves linearity of DEA and exhibits stronger discrimination power among the DMUs as compared to some existing approaches. Theoretically, the aggregate efficiency interval of each DMU lies between the components’ interval efficiencies. Further, the proposed approach is also applied to banks in India for proving its acceptability in practical applications. The performance of each bank is investigated in terms of two components: general business and bancassurance business for the years 2011–2013. The present study emphasized expanding pattern of bancassurance business in current market scenario with more percentage increase as contrasted to general business.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2540-1
Issue No: Vol. 259, No. 1-2 (2017)

• A survey of the standard location-routing problem
• Authors: Michael Schneider; Michael Drexl
Pages: 389 - 414
Abstract: In this paper, we define the standard LRP as a deterministic, static, discrete, single-echelon, single-objective location-routing problem in which each customer (vertex) must be visited exactly once for the delivery of a good from a facility, and in which no inventory decisions are relevant. We review the literature on the standard LRP published since the survey by Nagy and Salhi appeared in 2006. We provide concise paper excerpts that convey the central ideas of each work, discuss recent developments in the field, provide a numerical comparison of the most successful heuristic algorithms, and list promising topics for further research.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2509-0
Issue No: Vol. 259, No. 1-2 (2017)

• An EOQ model for decaying item with full advanced payment and conditional
discount
• Authors: Shayan Tavakoli; Ata Allah Taleizadeh
Pages: 415 - 436
Abstract: The classic economic order quantity model assumes that purchasing cost should be paid immediately after the delivery time. In practice, sometimes the vendors ask the buyers to prepay the entire or a percentage of the purchasing cost before delivery time. In this paper the buyer’s inventory control system for a decaying item under full prepayment scheme based on various conditions consisting of (1) no shortage, (2) full backordering shortage is allowed and (3) partial lost sale is permitted, are developed. Numerical analysis is provided to show the performance of the model and some managerial insights are presented based on the proposed solution technique and sensitivity analysis.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2510-7
Issue No: Vol. 259, No. 1-2 (2017)

• Model and metaheuristics for a scheduling problem integrating procurement,
sale and distribution decisions
• Authors: Simon Thevenin; Nicolas Zufferey; Rémy Glardon
Pages: 437 - 460
Abstract: This paper presents an integrated approach for short-term supply chain management (SCM) at a fast moving consumer goods production plant. The problem is to determine the production quantities, to provide a detailed production schedule, to trigger the relevant express deliveries of raw material, and to manage the distribution. We propose a linear integer model, which integrates all of these decisions within scheduling. To find high quality solutions in a reasonable amount of time, various solution methods are proposed, such as a greedy constructive heuristic, two tabu search metaheuristics, a basic variable neighborhood search and an enhanced one, which uses a variable shaking operator. Experiments on realistic instances show that the latter method is efficient and robust. This paper is a contribution to the SCM literature (indeed, only few references address the integration of short term decisions) and to the general metaheuristics field (as the variable neighborhood search paradigm is extended).
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2498-z
Issue No: Vol. 259, No. 1-2 (2017)

• Most unfavorable deductibles and coverage limits for multiple random risks
with Archimedean copulas
• Authors: Yinping You; Xiaohu Li
Pages: 485 - 501
Abstract: This paper has a further study on the insurer’s most unfavorable deductibles and coverage limits for interdependent random losses in the context of the zero-utility premium. For multiple random losses equipped with Archimedean copulas, we conduct stochastic comparison on the insurer’s most unfavorable deductibles and most unfavorable coverage limits, respectively. Also, we build the most unfavorable deductibles for risk-averse insurers. The main results extend and complement those related ones in the literature.
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2537-9
Issue No: Vol. 259, No. 1-2 (2017)

• Erratum to: On second-order duality of minimax fractional programming with
square root term involving generalized $${\varvec{B}}$$ B -
$${\varvec{(p,\,r)}}$$ ( p , r ) -invex functions
• Authors: Sonali; N. Kailey; V. Sharma
Pages: 503 - 503
PubDate: 2017-12-01
DOI: 10.1007/s10479-017-2502-7
Issue No: Vol. 259, No. 1-2 (2017)

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