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Authors:Yu Yu, Dariush Khezrimotlag Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In real-life applications, there generally exist Decision Makers (DMs) who have preferences over outputs and inputs. Choosing appropriate weights for different criteria by DMs often arises as a problem. The Best-Worst Method (BWM) in Multiple Criteria Decision-Making (MCDM) depends on very few pairwise comparisons and just needs DMs to identify the most desirable and the least desirable criteria. Unlike MCDM, Data Envelopment Analysis (DEA) does not generally assume a priority for an output (an input) over any other outputs (inputs). The link between DEA and MCDM can be introduced by considering Decision-Making Units (DMUs) as alternatives, outputs as criteria to be maximized, and inputs as criteria to be minimized. In this study, we propose a linear programming model to embed DEA and BWM appropriately. We first propose a modified BWM linear programming model to satisfy all conditions that DMs can assume. We then illustrate how a conventional DEA model can be developed to include the BWM conditions. From our approach, the MCDM problem to obtain the optimal weights of different criteria are measured. At the same time, the relative efficiency scores of DMUs corresponding to the MCDM criteria are also calculated. We provide the foundation of measuring the efficiency scores when most desirable and the least desirable inputs and outputs are known. To show the process of the proposed approach, a numerical example (including 17 DMUs with seven inputs and outputs) is also discussed. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-05-22T07:00:00Z DOI: 10.1142/S0217595923500100
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Authors:Shuiting Yu, Chenchen Wu, Chunming Xu Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. The traceability of Blockchain Technology (BT) has been implemented widely in many industries, but coupled with this fact is that more and more consumers focus on personal privacy information security. This paper mainly studies a BT-enabled operation system with customers’ privacy preferences and enterprises’ privacy protection. From the short-term perspective, we first investigate the impacts of different privacy attitudes from consumers on the optimal pricing and privacy protection decisions of enterprises in two scenarios with and without BT. Then, we give the conditions of enterprises adopting BT. Furthermore, from the long-term perspective, when privacy protection insurance is provided for risk-averse consumers, we also investigate the evolutionary stability strategies between enterprises and consumers using the evolutionary game theory. Finally, numerical analysis is adopted to verify the theoretical results and show that privacy protection and BT are important to the operation of enterprises and the purchasing behavior of consumers. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-05-17T07:00:00Z DOI: 10.1142/S021759592340002X
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Authors:Jinyu Dai Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. The CDT subproblem, which minimizes a quadratic function over the intersection of two ellipsoids, is a classical quadratic programming problem. In this paper, we study a method of solving CDT with a positive Lagrangian duality gap. An efficient splitting algorithm is proposed for finding the global optimal solutions. A cutting plane is firstly added to divide the feasible set of CDT into two subsets, and then two new quadratic programming problems with ellipsoidal and linear constraints are generated accordingly. Using the newly developed technique — second-order cone constraints to enhance the efficiencies of the SDP relaxation-based algorithms on the two subproblems, an optimal solution of CDT can be acquired by comparing the objective values of the two subproblems. Numerical experiments show that the new algorithm outperforms the two recent SDP relaxation-based algorithms, the two-parameter eigenvalue-based algorithm and the solver Gurobi 9.5 for certain types of CDT. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-05-12T07:00:00Z DOI: 10.1142/S0217595923500070
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Authors:Fangxia Wang, Baoyindureng Wu Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. For a positive real number [math], the [math]-Sombor index of a graph [math], introduced by Réti et al, is defined as SOk(G) =∑uv∈E(G)d(u)k + d(v)kk, where [math] denotes the degree of the vertex [math] in [math]. By the definition, [math] is exactly the Sombor index of [math], while [math] is the first Zagreb index of [math]. In this paper, for [math] we present the extremal values of the [math]-Sombor index of trees with some given parameters, such as matching number, the number of pendant vertices, diameter. This generalizes the relevant results on Sombor index due to Chen, Li and Wang ((2002). Extremal values on the Sombor index of trees, MATCH Communications in Mathematical and in Computer Chemistry, 87, 23–49). Handling [math] appears to be different for [math] in contrast to the case when [math]. To demonstrate this, we also characterize the extremal trees with respect to the [math] with matching number, the number of pendant vertices and diameter. In addition, three relevant conjectures are proposed. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-04-21T07:00:00Z DOI: 10.1142/S0217595923500021
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Authors:Mingzhu Yu, Qi Gao, Zelong Yi Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we examine the retailer’s information sharing decision in an authentic supply chain with a single supplier and a single retailer under different counterfeiter encroachment situations. We propose a Stackelberg game model to analyze the optimal wholesale price of the supplier, the optimal order quantity of the retailer and the optimal production quantity of the counterfeiter. We obtain the information sharing strategies of the retailer and analyze the impact of the counterfeiter on the authentic supply chain. It is revealed that: (1) under certain conditions, the retailer will voluntarily share information with the upstream supplier and (2) the existence of the counterfeiter may increase the profit of the authentic supply chain. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-04-17T07:00:00Z DOI: 10.1142/S021759592350001X
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Authors:Qingguo Bai, Guihao Wang, Di Liu, Zhenning Zhang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. While single-period stochastic inventory problems have been studied in academia and industry, the impacts of both carbon emissions reduction and partial distribution information have not been investigated. In this paper, we consider carbon emission reduction in a single-period inventory problem where both product price and demand are stochastic. When only partial information on the first and second moments of the two stochastic elements is specified, we use the max–min criterion to construct two optimization models under cap-and-trade and carbon tax policies. For each model, we prove the existence of the optimal robust decisions on production quantity and cleaning equipment investment. By comparing the profit and carbon emission between these two models, we identify certain conditions that improve the economic and environmental performance of the manufacturer. Finally, we conduct a numerical study to test the robustness of the optimal operational decisions under each carbon policy. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-31T07:00:00Z DOI: 10.1142/S0217595923400018
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Authors:Zhiwen Chen, Qiong Hao, Hong Huang, Cheng Qiao Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Learning a fast global model that describes the observed phenomenon well is a crucial goal in the inherently distributed Vehicular Networks. This global model is further used for decision-making, which is especially important for some safety-related applications (i.e., the altering of accident and warning of traffic jam). Most existing works have ignored the network overhead caused by synchronizing with neighbors, which inevitably delays the time for agents to stabilize. In this paper, we focus on developing an asynchronous distributed clustering algorithm to learn the global model, where cluster models, rather than raw data points, are shared and updated. Empirical experiments on a message delay simulator show the efficiency of our methods, with a reduced convergence time, declined network overhead and improved accuracy (relative to the standard solution). This algorithm is further improved by introducing a tolerant delay. Compared to the algorithm without delay, the performance is improved significantly in terms of convergence time (by as much as 47%) and network overhead (by around 53%) if the underlying network is geometric or regular. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-31T07:00:00Z DOI: 10.1142/S0217595923400043
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Authors:Feifeng Zheng, Yuhong Chen, Ming Liu, Yinfeng Xu Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. This work investigates a new semi-online scheduling problem with lookahead. We focus on job scheduling on two identical parallel machines, where deterministic online algorithms only know the information of [math] initial jobs (i.e., the initial-lookahead information), while the following jobs still arrive one-by-one in an over-list fashion. We consider makespan minimization as the objective. The study aims at revealing the value of knowing [math] initial jobs, which are used to improve the competitive performance of those online algorithms without such initial-lookahead information. We provide the following findings: (1) For the scenario where the [math] initial jobs are all the largest jobs with length [math], we prove that the classical LIST algorithm is optimal with competitive ratio [math]; (2) For the scenario where the total length of these [math] jobs is at least [math], we show that any online algorithm has a competitive ratio at least 3/2, implying that the initial-lookahead knowledge is powerless since there exists a 3/2-competitive online algorithm without such information; (3) For the scenario where the total length of these [math] jobs is at least [math] ([math]), we propose an online algorithm, named as LPT-LIST, with competitive ratio of [math], implying that the initial-lookahead information indeed helps to improve the competitiveness of those online algorithms lacking such information. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-31T07:00:00Z DOI: 10.1142/S0217595923500033
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Authors:Yanan Song, Zexin Yue, Junlin Chen, Xiaobo Zhao Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we consider a newsvendor system with strategic customers, who are boundedly rational and risk averse in terms of buying during the selling season or waiting for a clearance sale with price discounts. The newsvendor’s decision is to determine the optimal stock quantity. An optimization problem is formulated with the incorporation of competition among strategic customers with private product value information. We embed risk aversion within the quantal response equilibrium to characterize the strategic customer behavior. The influences of the decision biases of strategic customers on the newsvendor’s decision and profit are discussed. We find that the risk aversion considered alone always benefits the newsvendor. However, the bounded rationality considered alone benefits the newsvendor conditionally. Combining the two behavioral factor influences, the decision biases cause the newsvendor to order more and be better off when the critical fractile is high but to order less and be worse off when the critical fractile is low. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-31T07:00:00Z DOI: 10.1142/S0217595923500045
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Authors:Kellen D. Endler, Cassius T. Scarpin, Maria T. A. Steiner, Alexandre C. Choueiri Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. The vehicle routing problem (VRP) and its variants are a class of network problems that have attracted the attention of many researchers in recent years, owing to their pragmatic approach to solving issues in logistics management. Most surveys/reviews of the extant literature often focus on specific variants or aspects of the VRP. However, a few reviews of the overall VRP literature are available. The focus of these papers is to identify which VRP literature characteristics are the most popular in recent studies. To this end, we analyze 229 articles published between 2015 and 2017. We provide a systematic literature review evaluating the Scenario Characteristics and Problem Physical Characteristics that are most frequently addressed by VRP researchers, the Type of Study and Data Characteristics that they address, the most cited works that constitute the theoretical pillars of the field, and details of three specific problem variants that have been studied extensively in recent years and their opportunities for future research. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-25T07:00:00Z DOI: 10.1142/S0217595922500464
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Authors:Yifu Feng, Zonghai Hu, Rui Si, Ji-Bo Wang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. This paper concentrates on the single-machine scheduling problem with past-sequence-dependent setup times and general truncated learning effects, where the job processing times are non-increasing function of their positions in a sequence. Under common, slack and different (unrestricted) due-date assignments, our goal is to minimize the weighted sum of number of early/tardy jobs and due-date assignment cost, where the weight is not related to the job but to a position, i.e., the position-dependent weight. Under the three due-date assignments, some optimal properties and three optimal solution algorithms are proposed to solve these problems, respectively. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-21T07:00:00Z DOI: 10.1142/S0217595923500069
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Authors:Ying Chen, Yi Xu, Guiqing Zhang, Yongxi Cheng Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we study a single machine scheduling problem with due date assignment under a group technology environment. The due dates of jobs are assignable according to the following three methods: the common (CON) due date assignment, the slack (SLK) due date assignment, and the different (DIF) due date assignment. Our objective is to determine a group sequence and job sequences within all groups, together with a due date assignment, to minimize a total cost function including earliness, tardiness, due date assignment and flow time costs, in which all unit costs are different and position-dependent. We present a unified [math] time algorithm to solve the problem for all the three due date assignment methods. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-18T07:00:00Z DOI: 10.1142/S0217595923400079
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Authors:Cuixia Miao, Jiaxin Song, Yuzhong Zhang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. We consider the time-dependent scheduling with proportional and delivery times on a single machine. Three models of the processing times are addressed here, they are proportional deterioration, proportional-linear shortening and proportional-linear increasing. The objective is to minimize the time by which all jobs are delivered. For the first model, we prove that the problem is polynomial solvable when jobs have identical release dates. When jobs arrive dynamically, we first give the proof of the NP-hardness and present a two-approximation algorithm. Then we propose a fully polynomial time approximation scheme for the case where the number of distinct release dates is a constant by applying the “rounding-the-input-data” technique. For the second and third models, when jobs have identical release dates, we prove that they are polynomial solvable, when jobs have different release dates, we present two-approximation algorithms for each of them. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-11T08:00:00Z DOI: 10.1142/S0217595922400152
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Authors:Sainan Guo, Yannan Chen, Yaping Mao, Xiaoyan Zhang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we consider two single-processor online scheduling problems with an unexpected breakdown. Speaking specifically, there is a group of nonresumable jobs being processed on the single processor. Note that the breakdown will emerge on the processor suddenly, which signifies that its beginning time and its length are unknown in advance. In this study, we are interested in scheduling the jobs so as to minimize the maximum weighted completion time. Most noticeably, when all jobs respect an agreeable condition, i.e., for each two jobs [math] and [math], [math] means that [math], we design an optimal online algorithm. In addition, for the general version, we propose an online algorithm with a competitive ratio of at most 2. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-11T08:00:00Z DOI: 10.1142/S0217595923500057
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Authors:Jin-Cheng Lu, Mei-Juan Li Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Decision-maker (DM) can assign the weights of the distance measures in the relative closeness of technique for order preference by similarity to ideal solution (TOPSIS) for achieving his/her desirable ranking of alternatives. This phenomenon is called strategically setting distance measure weights in this study, which may affect the fairness of the results. In order to prevent this phenomenon, the idea of data envelopment analysis (DEA) is introduced to determine the objective weights of distance measures, and an improved TOPSIS is proposed in this study. The proposed method not only determines weights of the distance measures from an objective perspective and achieves the fully ranking of alternatives, but also provides the directions for improvement. Moreover, in comparison with the other methods, the advantages of the proposed method are analyzed, and the meanings and properties of the new relative closeness are discussed and proved. Finally, an example of evaluating the innovation development of high-tech industries in central and western regions of China is investigated to illustrate the effectiveness and the usefulness of the proposed method. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-09T08:00:00Z DOI: 10.1142/S0217595922500348
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Authors:Gaoxi Li, Liping Tang, Liying Liu, Zhongping Wan Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. The mathematical program with switching constraints (MPSC), which has been introduced recently, is a difficult class of optimization problems. The reason for the difficulty is that the existence of the switching constraint makes the standard constraint qualifications invalid at local minimizers. This paper proposes the Wolfe-type dual (WD) model of this problem without switching constraints. Under the assumptions of convexity and strict convexity, we derive the weak, strong, converse, restricted converse, and strict converse duality results between MPSC and WD. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-09T08:00:00Z DOI: 10.1142/S0217595922500439
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Authors:Raoul Müller, Anita Schöbel, Dominic Schuhmacher Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we study a generalized version of the Weber problem of finding a point that minimizes the sum of its distances to a finite number of given points. In our setting, these distances may be cut off at a given value [math], and we allow for the option of an empty solution at a fixed cost [math]. We analyze under which circumstances these problems can be reduced to the simpler Weber problem, and also when we definitely have to solve the more complex problem with cutoff. We furthermore present adaptions of the algorithm of Drezner, Mehrez and Wesolowsky (1991 [The facility location problem with limited distances. Transportation Science, 25(3), 183–187, INFORMS]) to our setting, which in certain situations are able to substantially reduce computation times as demonstrated in a simulation study. The sensitivity with respect to the cutoff value is also studied, which allows us to provide an algorithm that efficiently solves the problem simultaneously for all [math]. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-09T08:00:00Z DOI: 10.1142/S0217595922500452
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Authors:Zohre Aminifard, Saman Babaie-Kafaki, Nasrin Mirhoseini Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In an effort to make modification on the classical Polak–Ribière–Polyak method, Wei et al. suggested an efficient nonlinear conjugate gradient method which possesses the sufficient descent property when the line search fulfills the strong Wolfe conditions (by restricting the line search parameters). Here, we develop a three-term extension of the method which satisfies the sufficient descent condition independent of the line search. Also, under a backtracking Armijo-type line search, we establish global convergence of the method without convexity assumption. Using a scalar approximation of the Hessian of the objective function, we suggest an acceleration scheme that can be used in the iterative line search methods of unconstrained optimization. At last, practical merits of the proposed method are investigated by numerical experiments on a set of CUTEr test functions as well as the well-known image restoration problem. The results show numerical efficiency of the method. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-03-09T08:00:00Z DOI: 10.1142/S0217595922500476
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Authors:Na Xu, Fan-Yun Meng, Li-Ping Pang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Mathematical program with vertical complementarity constraints (MPVCC) plays an important role in economics and engineering. Due to the vertical complementarity structure, most of the standard constraint qualifications fail to hold at a feasible point. Without constraint qualifications, the Karush–Kuhn–Tucker (KKT) conditions are not necessary optimality conditions. The classical methods for solving constrained optimization problems applied to MPVCC are likely to fail. It is necessary to establish efficient algorithms for solving MPVCC from both theoretical and numerical points of view. We present an algorithm to obtain stationarity of MPVCC by solving a sequence of Scholtes regularized problems. We consider the Scholtes regularization method with the sequence of approximate KKT points only. We prove that, under strictly weaker constraint qualifications, the accumulation point of the approximate KKT points is Clarke (C-) stationary point. In particular, we can get Mordukhovich (M-) or strongly (S-) stationary point under additional assumptions. From these results, we apply an augmented Lagrangian method to obtain a solution of MPVCC and give the convergence analysis. In particular, the accumulation point of the generated iterates is an S-stationary point if some boundedness conditions hold. The numerical results show that it is an effective way to solve MPVCC. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-02-08T08:00:00Z DOI: 10.1142/S0217595922500427
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Authors:Thanh-Hung Pham Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we prove that the Henig global proper efficient solution map and the Henig global proper efficient perturbation map of a parametric vector optimization problem are second-order semi-differentiable with index [math] under some suitable qualification conditions. Several examples are given to illustrate the obtained results. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-01-25T08:00:00Z DOI: 10.1142/S0217595922500415
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Authors:Min Ji, Kaili Qi, T. C. E. Cheng, Yiwei Jiang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. We present a unified approach to single-machine scheduling with position-based processing times, an availability constraint, and job rejection. The approach uses two general position-based processing time functions to model both the learning and aging effects in scheduling. In addition, taking machine availability and job rejection into consideration, the models are more realistic, which seek to minimize the sum of the makespan of the accepted jobs and the total penalty of the rejected jobs. We present fully polynomial-time approximation schemes to address the two NP-hard problems. Citation: Asia-Pacific Journal of Operational Research PubDate: 2023-01-05T08:00:00Z DOI: 10.1142/S0217595922500403
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Authors:Yajing Wang, Dongyue Liang, Weihua Yang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. The unbalanced assignment problem (UAP) aims to distribute a set of jobs to some workers. The cost of the jobs is different when they are distributed to different workers. The goal is: (1) minimizing the total cost of arranging jobs to workers; (2) making the distribution of jobs as even as possible among all the workers. We transform the UAP into a min-cost network flow problem with squared terms, and apply the belief propagation (BP) algorithm to deal with it. We prove that, when the min-cost network flow problem has a unique optimal solution, the BP algorithm converges to the optimal solution within [math] iterations, where [math] represents the number of vertices of the flow network, [math] is the difference between value of the optimal solution and the second optimal solution and [math] is the maximum value of the terms of the objective function. Next, we prove that BP converges to the optimal solution in [math] operations, where [math] represents the number of edges and [math] is the tight upper bound of the slope of the terms of the objective function. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-12-10T08:00:00Z DOI: 10.1142/S0217595922500373
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Authors:Liqun Qi, Yisheng Song, Xinzhen Zhang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we seek analytically checkable necessary and sufficient condition for copositivity of a three-dimensional symmetric tensor. We first show that for a general third-order three-dimensional symmetric tensor, checking copositivity is equivalent to solving a quartic equation and some quadratic equations. All of them can be solved analytically. Thus, we present an analytical way to check copositivity of a third-order three-dimensional symmetric tensor. Then, we consider a model of vacuum stability for [math] scalar dark matter. This is a special fourth-order three-dimensional symmetric tensor. We show that an analytically expressed necessary and sufficient condition for this model bounded from below can be given, by using a result given by Ulrich and Watson in 1994. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-11-28T08:00:00Z DOI: 10.1142/S0217595922500324
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Authors:He Huang, Nuo Qi, Xin-He Miao Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we consider a system of inequalities associated with circular cones. By constructing a new smoothing function, the problem is reformulated as a system of parameterized smooth equations. In addition, we suggest a Newton-type algorithm for solving the smooth equations so that a solution of the problem concerned is found. In particular, the algorithm is proved to be globally and locally quadratically convergent under suitable conditions. The preliminary numerical results demonstrate that the algorithm is effective. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-11-22T08:00:00Z DOI: 10.1142/S0217595922500178
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Authors:Song Pu, Chang Xia Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. This paper studies a novel form of last-mile delivery that combines delivery optimization of E-commerce and Online-to-Offline (O2O) parcels. While O2O parcels must first be picked up from O2O shops before being delivered to the appropriate customers, E-commerce parcels are delivered to customers from a predetermined number of depots. The goal is to use the same fleet of vehicles to provide integrated delivery services for various merchant types. We propose a branch-and-price algorithm based on the set partitioning formulation, where the pricing problem is solved by a label-setting algorithm. Several acceleration techniques including elementary path relaxation, ng-path relaxation and decremental space search are designed to speed up the price problem. Both the conventional dataset used in the literature and a real-world database with up to 75 clients are utilized to test the performance of the suggested method, demonstrating its efficacy. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-11-22T08:00:00Z DOI: 10.1142/S0217595922500269
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Authors:Bin Liu, Dong Liang, Feimin Zhong, Jinxing Xie Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Cooperative advertising (coop-ad) programs with both accrual rates and participation rates are popularly adopted in practice by manufacturers and retailers to share advertising expenditures. However, results from extant literature show that the accrual rates always negatively impact the manufacturers’ performances, indicating a gap between theory and practice. In this paper, we study a coop-ad program in a distribution channel consisting of a manufacturer and a retailer with risk preferences under demand uncertainty. When both the channel members are risk-neutral, we show that an elaborately specified accrual rate can help reach channel coordination, although the accrual rate always negatively impacts the manufacturer’s performance. When the manufacturer is risk-averse and the retailer is risk-neutral, the accrual rate may positively impact the manufacturer’s performance, and in particular, the manufacturer does prefer a coop-ad program with an accrual rate if his risk-averse level is high and/or the demand volatility is high. When both the channel members are risk-averse, numerical examples illustrate that an accrual rate may benefit both members when the retailer has high profitability and low risk-averse level. These findings, seemingly never reported in the literature, provide plausible explanations for the fact that accrual rates are usually included in coop-ad programs in real-world practice. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-10-26T07:00:00Z DOI: 10.1142/S0217595922500385
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Authors:Mazhar Arikan, Sercan Demir, Murat Erkoc Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we study optimal procurement policies with advance contracting option over a finite multi-period horizon for a seasonal product. In this setting, each period is defined by the time between two consecutive inventory replenishment stages where demand is not stationary across periods. Demand for the product in each period is stochastic whose probabilistic distribution is a function of the market signal received right before the beginning of the selling season. The firm receives price discounts by making quantity contracts in advance of the selling season and thus, before the realization of the market signal. Replenishment costs vary across periods during the selling season. We investigate optimal combination of advance contracting and expedited replenishment policies using stochastic dynamic programming. Our research is primarily motivated by applications in the cruise line industry where contracts are made before the final number of bookings is realized and additional purchases can be made at ports of call with varying local prices. Our results show that optimal replenishment policies follow order-up-to policies and there is a unique advance contract amount that minimizes the expected costs over the planning horizon. We provide a numerical sensitivity analysis to investigate the effects of replenishment prices, demand volatility, and disparity between periods in terms of demand on the advance contract amount, replenishments from the spot markets, service levels, and the overall expected cost. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-10-17T07:00:00Z DOI: 10.1142/S0217595922500312
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Authors:Yuanyuan Zhao, Lei Fang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Most supply chains in reality are composed of multiple enterprises which are independent individuals in terms of organizational structures and operating modes. From the perspective of performance evaluation, optimizing each enterprise’s efficiency independently will probably result in undesired inventory of intermediate products in the supply chain. Taking the two-stage supply chain where the outputs from the upstream supplier are taken as the inputs for the downstream manufacturer as an example, this paper introduces enterprises’ relative dominance into allocating the responsibility of inventory management between two decentralized enterprises. To motivate these enterprises to adopt the allocation strategy, this paper takes the loss aversion of enterprises into account to reveal the utility subjectively perceived by each decentralized enterprise insisting on independence instead of cooperation. Subsequently, a DEA-based cooperative model is developed to readjust the production processes of two decentralized enterprises. We find that adjusting the relevant parameters is able to explore the relationship between the proposed model and the non-cooperative model and the relationship between the proposed model and the centralized model. Finally, a practical example of coordinating sustainable supply chains is applied to illustrate the effectiveness of the proposed model. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-10-17T07:00:00Z DOI: 10.1142/S0217595922500397
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Authors:Mehdi Soltanifar Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Multi-attribute decision-making (MADM) methods are widely used by decision makers as decision support tools. Most MADM methods have shortcomings in the solution process that combined with other decision making methods can eliminate these shortcomings or improve the performance of the method. One of the methods that can be used to improve MADM methods is preferential voting, which is actually a linear programming (LP) model with weight restrictions. The Kemeny Median Indicator Ranks Accordance (KEMIRA) is one of the most modern MADM methods; in this paper, we provide an improved version in this relative, by utilizing the concept of preferential voting. The new model, in being implemented on a real-world problem, will be compared to the previous method and ultimately some of its advantages will be rendered. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-10-13T07:00:00Z DOI: 10.1142/S0217595922500245
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Authors:Ke Chen, Songqiao Han, Hailiang Huang, Min Ji Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we study a single machine scheduling problem with group-dependent due window assignment and further incorporate autonomous and induced learning effects. Here, autonomous learning refers to learning by doing, while induced learning denotes that proactive investments can promote the learning effect, i.e., the learning effect is controllable. The proactive spending could include any management efforts like professional training programs, among others. The objective is to find optimal strategies of due window assignments, sequence of groups and jobs, and level of induced learning that optimize the total cost comprising the due window-related penalty costs and the investment cost. We present a polynomial-time algorithm capable of solving this problem and an improved idea to further reduce the time complexity. In addition, a detailed numerical example is conducted. Our study shows that the learning effect can be tuned to fit the demand of the manufacturing system better and lead to a more flexible operating system. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-10-13T07:00:00Z DOI: 10.1142/S0217595922500257
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Authors:Yang Xu, Yelin Fu, Yu Chen, Kin Keung Lai Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. This paper proposes a group decision making model with individual preferences to investigate the multicriteria ABC inventory classification problem. We first propose a preliminary group decision matrix by means of identifying the individual preference among the classification criteria as a typical decision maker; then analyze the endogenous individual preference structure in terms of exploring the preferential difference and preferential priority, a revised group decision matrix is therefore presented; thirdly, make the use of SMAA-2 to derive the holistic acceptability index for classifying the SKUs. A satisfaction index is developed to manifest the merits of proposed method. A numerical illustration using the data drawn from previous studies is performed to indicate the applicability and feasibility of our method. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-10-13T07:00:00Z DOI: 10.1142/S0217595922500361
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Authors:Nazih Abderrazzak Gadhi, Mohamed Ohda Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this note, we establish sufficient optimality conditions in terms of upper convexificators for a robust multiobjective optimization problem (UCP) involving nonsmooth/nonconvex real-valued functions. For this purpose, two kinds of generalized convex functions are defined in terms of upper convexificators. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-10-03T07:00:00Z DOI: 10.1142/S0217595922500270
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Authors:Tran Hoai Ngoc Nhan, Kien Trung Nguyen, Huong Nguyen-Thu Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. The classical reverse 1-median problem on trees is to adjust the edge lengths within a budget so as to reduce the 1-median function at a predetermined vertex as much as possible. This paper concerns the corresponding problem with uncertain vertex weights presented by linear functions. Moreover, we use the minmax regret criterion to measure the maximum loss of a feasible solution with respect to the worst-case scenario. The regarding problem is called the minmax regret reverse 1-median problem on trees. We first partition the set of scenarios into parts such that the optimal solution of the corresponding reverse 1-median problem does not change in each part. Then the problem can be reformulated as the minimization of a quadratic number of affine linear functions. We finally develop a greedy algorithm that solves the problem in [math] time where [math] is the number of vertices in the underlying tree. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-10-03T07:00:00Z DOI: 10.1142/S0217595922500336
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Authors:Akram Esmaeili Avval, Farzad Dehghanian, Mohammadali Pirayesh Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Among the carbon regulation policy schemes, the cap-and-trade has received more attention because of its efficiency and flexibility. Two primary challenges with the cap-and-trade scheme are determining the correct cap and carbon trading price in the carbon market. This paper presents a bi-level model to investigate these two challenges in the cap-and-trade scheme formed between multiple supply chains and the government. At the first level, the government minimizes the cap in such a way that the costs of the supply chains do not rise too much. At the second level, the supply chains minimize their costs according to their cap and trade the dedicated allowances. An exact and a heuristic method are developed to solve the bi-level model. The computational results on a set of randomly generated instances show the effectiveness of the presented heuristic. Sensitivity analysis demonstrates that the government should choose proper amounts of caps to balance costs and environmental benefits. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-09-05T07:00:00Z DOI: 10.1142/S0217595922500191
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Authors:Yining Sun, Li Wang, Juhe Sun, Bin Wang, Yanhong Yuan Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we construct an implementable augmented Lagrangian method to solve second-order cone constrained variational inequalities (SOCCVI) problem. By considering a special optimization problem that has the same solution as the SOCCVI problem, we obtain different equivalent transformation forms of the SOCCVI problem. Using the equivalent transformation forms and the properties of the projection operators, the augmented Lagrangian method can be established and its global convergence is proved. The inexact Newton method is used to solve the inner problems which arise from the augmented Lagrangian method for solving the numerical examples. Numerical results for three examples are reported to verify the effectiveness of the augmented Lagrangian method for obtaining approximate solutions. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-09-05T07:00:00Z DOI: 10.1142/S0217595922500300
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Authors:Xiaoyue Zhang, Wenqiang Dai, Xiaoqiang Cai, Xiaoyu Zhou Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we seek to provide real-time replenishment policy for a capacitated company that faces an exogenous demand and has to procure and store sufficient quantities of certain items with uncertain procurement prices. The objective is to minimize the total cost of the procuring cost and inventory holding cost without stock out. Motivated by the fact that a large variability in the price process often makes forecasting difficult, in contrast to the traditional approaches of the stochastic inventory theory, we study this problem from the perspective of competitive analysis who is free of any price distribution assumption. We propose an online replenishment model, which generalizes several previous online models. We give a real-time replenishment policy whose decisions are made based entirely on the past and present prices and the current inventory level. We prove that our policy achieves superior performance, and outperforms all of the previous theoretical results. Furthermore, we present the numerical studies to show that our replenishment policy achieves an even better empirical performance. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-08-26T07:00:00Z DOI: 10.1142/S0217595922500294
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Authors:Sachin Rastogi, Akhlad Iqbal, Sanjeev Rajan Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Taking into consideration gH-symmetrical derivative, we discuss Fritz John type optimality conditions for E-convex functions in interval-valued optimization problems. By a suitable example, we show that gH-symmetrical derivative is an extension of gH-derivative. We use LU type of order relation in this context. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-07-29T07:00:00Z DOI: 10.1142/S0217595922500117
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Authors:Fei Teng, Si-Wen Luo, Dan-Yang Lv, Ji-Bo Wang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we consider scheduling problems with slack (different) due-window assignment and time-dependent processing times. The processing time functions are all a proportional linear increasing function of time. On a single-machine setting, the goal is to minimize a cost function that includes earliness, tardiness, due-window starting time and size, and the number of early and tardy jobs. Some relevant optimality properties and polynomial time solution algorithms are proposed to solve these two problems. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-07-29T07:00:00Z DOI: 10.1142/S0217595922500221
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Authors:Lei Fang, Yi Gao Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. This paper investigates a dual-channel supply chain which consists of a capital-constrained manufacturer and an e-commerce platform. The manufacturer sells its products through an offline direct channel and an online platform. The platform can serve as a marketplace or a reseller for the manufacturer, while the platform provides online finance to the manufacturer. We discuss the equilibrium decisions of the manufacturer and the platform when the platform serves as two different roles. We find that when the total production quantity of the manufacturer who with an online marketplace channel exceeds a threshold, the manufacturer tends to choose the platform’s marketplace role for the online channel, unless the wholesale price and the upper limit of demand are high. When production quantity is below this threshold, unless the wholesale price and the upper limit of demand are low, the manufacturer tends to choose the platform’s reseller role for the online channel. The platform tends to choose the role whose production quantity exceeds the threshold. If both are exceeded, the platform chooses the marketplace role when the wholesale price is low, and if both are not exceeded, the marketplace role is better when the wholesale price is high. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-07-25T07:00:00Z DOI: 10.1142/S0217595922500208
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Authors:Feifeng Zheng, Kaiyuan Jin, Yinfeng Xu, Ming Liu Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. This work investigates an unrelated parallel machine scheduling problem in the shared manufacturing environment. Based on practical production complexity, five job and machine-related factors, including job splitting, setup time, learning effect, processing cost and machine eligibility constraint, are integrated into the considered problem. Parallel machines with uniform speed but non-identical processing capabilities are shared on a sharing service platform, and jobs with different types can only be processed by the machines with matching eligibilities. The platform pays an amount of processing cost for using any machine to process the jobs. To balance the processing cost paid and the satisfaction of customers, we aim to minimize the weighted sum of total processing cost and total completion time of jobs in the considered problem. We establish a mixed integer linear programming model, and provide a lower bound by relaxing the machine eligibility constraint. The CPLEX solver is employed to generate optimal solutions for small-scale instances. For large-scale instances, we propose an efficient heuristic algorithm. Experimental results demonstrate that for various instance settings, the proposed algorithm can always produce near optimal solutions. We further present several managerial insights for the shared manufacturing platform. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-07-25T07:00:00Z DOI: 10.1142/S0217595922500233
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Authors:Ermei Wang, Lin Li, Kuan Yang, Yinggao Zhou Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Considering the real dilemma of deteriorating items, we explore how to find a balance between the conflicting achievements of enhancing flexibility and reducing costs. We propose a general dynamic model to penetrate customer orders by decoupling point with objective to minimize the cost. The closed forms of optimal solutions are obtained for companies to deal with the integrated problem of customer order decoupling point (CODP) decision and production–inventory plan simultaneously. Applications and numerical experiments are performed to illustrate practical insights for managers. The results show that the truth of zero-inventory policy is to avoid unnecessary inventory instead of absolutely no inventory. The CODP will shift forward with the increasing of customer demand rate and shift backward with the increasing of deterioration rate under the production smoothing policy. However, although it encounters the same changes of demand, the CODP moves with a smaller extent in high deterioration rate than in low. In addition, we find that during the growth phase of product life cycle, the increase of time-sensitive degree of demand is coupled with forward shifting of CODP; while during the decline phase, it is coupled with CODP backward shifting. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-07-11T07:00:00Z DOI: 10.1142/S021759592250021X
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Authors:Xinyu Sun, Xin-Na Geng, Jiayin Wang, Tao Liu Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. We study single-machine bicriteria scheduling problems with position-dependent weights. Due date costs and penalty costs can affect the decision-maker’s profit. Therefore, how to optimize the benefits and balance of these costs for decision-makers is the focus of this research. This paper discusses three models: weighted-sum scheduling problem, constrained scheduling problem, Pareto scheduling problem. It analyzes the properties of bicriteria schedule, determines the optimal due dates (usually referred to as different due dates: DIF), and gives the corresponding polynomial solvable algorithms. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-05-25T07:00:00Z DOI: 10.1142/S021759592250018X
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Authors:Feng Fu, Shuangying Chen, Wei Yan Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. The remanufacturing industry is experiencing a gradual increase in international trade. Accordingly, manufacturers are encountering a multitude of regulations in this cross-border trade of remanufactured products, such as import prohibitions/bans, environmental regulations, and tariff barriers. In this paper, we investigated the implications of exporting remanufactured products to the international market with or without trade regulations. Our analysis reveals that, although the international market for remanufacturing invariably benefits the manufacturer, trade regulations are a disadvantage to remanufactured exports. Thus, while the quality of remanufactured products increases, the adverse effect of trade regulations could be weakened. Additionally, we reveal that trade regulations may be detrimental to the environment with a higher rate of used core collection and disposal impact. Thus, policymakers should take care to regulate the international market for remanufactured goods rather than implementing a one-size-fits-all solution. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-05-04T07:00:00Z DOI: 10.1142/S0217595922500166
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Authors:Hongjun Peng, Wenting Sun, Tao Pang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, we consider a dual-channel farming supply chain with two farmers and one distributor, where agriculture products produced by farmers have different quality levels. Farmers sell high-quality products to supermarkets and normal-quality products to small retail markets, respectively. Three scenarios are investigated: decentralized selling through the distributor to supermarkets (the DD mode); centralized selling through the distributor to supermarkets (the CD mode); centralized selling directly to supermarkets (the CS mode). Under the CS mode, farmers need to bear some extra sale cost such as inventory and transportation cost. We derive farmers’ optimal strategies of production effort and quality investment. It turns out that as farming scale expands, farmers’ production effort decreases, while quality investment increases. Moreover, two farmers’ quality investments are the highest under the CS mode and the least under the DD mode. Further analysis indicates that farmers’ total profits are generally the highest under the CS mode, but farmers obtain the highest profits under the CD mode if farmers’ extra sale cost under the CS mode exceeds a certain level. Therefore, to improve farmers’ welfare and agriculture products’ quality simultaneously, the CS mode may be the best choice in most cases, and it leads to a “win–win” situation for farmers and consumers. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-04-26T07:00:00Z DOI: 10.1142/S0217595922500154
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Authors:Bo Zhang, Yuelin Gao Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. Founded on the idea of subdividing the [math]-dimensional output space, a branch-and-bound algorithm for solving the sum-of-linear-ratios(SLR) problem is proposed. First, a two-stage equivalent transformation method is adopted to obtain an equivalent problem(EP) for the problem SLR. Second, by dealing with all nonlinear constraints and bilinear terms in EP and its sub-problems, a corresponding convex relaxation subproblem is obtained. Third, all redundant constraints in each convex relaxation subproblem are eliminated, which leads to a linear programming problem with smaller scale and fewer constraints. Finally, the theoretical convergence and computational complexity of the algorithm are demonstrated, and a series of numerical experiments illustrate the effectiveness and feasibility of the proposed algorithm. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-03-24T07:00:00Z DOI: 10.1142/S0217595922500105
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Authors:Arshpreet Kaur, Mahesh Kumar Sharma, Izhar Ahmad Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. We introduce new classes of higher-order functional, termed higher-order [math]convex and higher-order [math]convex functionals. These classes are illustrated by nontrivial examples. A pair of higher-order multiobjective symmetric fractional variational programs with cone constraints and fixed boundary conditions is formulated. Appropriate duality results are discussed utilizing the aforementioned assumptions. The results in this paper are generalizations of the results already existing in literature. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-03-10T08:00:00Z DOI: 10.1142/S0217595922500087
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Authors:Zhi-Ang Zhou, Min Kuang Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print. In this paper, our purpose is to use the improvement set to investigate the scalarization and optimality conditions of [math]-globally proper efficient solution for the set-valued equilibrium problems with constraints. First, the notion of [math]-globally proper efficient solution for set-valued equilibrium problems with constraints is introduced in locally convex Hausdorff topological spaces. Second, the linear scalarization theorems of [math]-globally proper efficient solution are derived. Finally, under the assumption of nearly [math]-subconvexlikeness, the Kuhn–Tucker and Lagrange optimality conditions for set-valued equilibrium problems with constraints are obtained in the sense of [math]-globally proper efficiency. Meanwhile, we give some examples to illustrate our results. The results obtained in this paper improve and generalize some known results in the literature. Citation: Asia-Pacific Journal of Operational Research PubDate: 2022-02-28T08:00:00Z DOI: 10.1142/S0217595922500099
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