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modeling and Solving a Multi-Period Inventory Fulfilling and Routing Problem for Hazardous Materials

Journal of Systems Science & Complexity 2020年第3期33卷 760-782页

作者： HU Hao LI Jian LI Xiang SHANG Changjing School of Economics and Management Shijiazhuang Tiedao UniversityShijiazhuang 050000China College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China Research Base of Beijing Modern Manufacturing Development College of Economics and ManagementBeijing University of TechnologyBeijing 100124China College of Economics and Management Beijing University of Chemical TechnologyBeijing 100029China Department of Computer Science Institute of MathematicsPhysics and Computer ScienceAberystwyth UniversityAberystwyth SY233DBUK

Any potential damage may be severe once an accident occurs involving hazardous *** is therefore important to consider the risk factor concerning hazardous material supply chains,in order to make the best inventory routing *** paper addresses the problem of hazardous material multi-period inventory routing with the assumption of a limited production capacity of a given *** goal is to achieve the manufacturer's production plan,the retailer's supply schedule and the transportation routes within a fixed *** the distribution of hazardous materials over a certain period is essentially a multiple travelling salesmen problem,the authors formulate a loadingdependent risk model for multiple-vehicle transportation and present an integer programming model to maximize the supply chain *** improved genetic algorithm considering two dimensions of chromosomes that cover the aforementioned period and supply quantity is devised to handle the integer programming *** experiments carried out demonstrate that using the proposed multiperiod joint decision-making can significantly increase the overall profit of the supply chain as compared to the use of single period decision repeatedly,while effectively reducing its risk.

关键词： Genetic algorithm integer programming model limited production capacity multi-period inventory routing problem

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Multi-stage optimization model for hesitant qualitative decision making with hesitant fuzzy linguistic preference relations

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APPLIED INTELLIGENCE 2020年第1期50卷 222-240页

作者： Wu, Peng Zhou, Ligang Chen, Huayou Tao, Zhifu Anhui Univ Sch Math Sci Hefei 230601 Anhui Peoples R China Nanjing Univ Informat Sci & Technol China Inst Mfg Dev Nanjing 210044 Jiangsu Peoples R China Anhui Univ Sch Econ Hefei 230601 Anhui Peoples R China

Hesitant fuzzy linguistic preference relation (HFLPR) as a new preference relation is introduced to express the decision makers' (DMs') hesitant preference information for each pairwise comparison between different alternatives or criteria. In this paper, the priority vector and consistency of HFLPR are discussed based on a two-stage optimization and multiplicative consistency. Based on the original hesitant preference information, the multiplicative consistency index of an HFLPR is defined to measure the consistency level of the HFLPR. For an unacceptable multiplicative consistent HFLPR, a goal programming model, which is an integer optimization model, is developed to derive an acceptable, multiplicative, consistent HFLPR. According to probability sampling, a linguistic preference relation (LPR) with the best consistency level and an LPR with the worst consistency level with regard to an HFLPR are defined. Combining the two LPRs, a two-stage optimization framework is constructed to obtain the HFLPR's priority vector, which considers the DM's risk preference. A multi-stage optimization approach is proposed to solve decision-making problems by integrating the goal programming model and the two-stage optimization framework. Two real life problems are analyzed to show the feasibility of the proposed approach.

关键词： Decision making Hesitant fuzzy linguistic preference relations Multiplicative consistency Priority vector integer programming model

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Group decision making based on multiplicative consistency and consensus of fuzzy linguistic preference relations

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INFORMATION SCIENCES 2020年 509卷 71-86页

作者： Zhang, Zhiming Chen, Shyi-Ming Wang, Chao Hebei Univ Coll Math & Informat Sci Hebei Key Lab Machine Learning & Computat Intelli Baoding 071002 Peoples R China Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei Taiwan Hebei Univ Engn Sch Management Engn & Business Intelligent Comp & Financial Secur Lab Handan 056038 Peoples R China

Fuzzy linguistic preference relations (FLPRs) are an efficient way to express qualitative judgments of decision makers (DMs). This paper proposes a new group decision making (GDM) method based on the multiplicative consistency and consensus of FLPRs. First, we propose the concepts of consistency index and acceptable multiplicative consistent FLPRs. Then, we propose a method to improve the consistency of a FLPR, by which an acceptable multiplicative consistent FLPR is derived. Subsequently, we propose the consensus index for measuring the agreement among DMs. With respect to some FLPRs have an unacceptable multiplicative consistency and an unacceptable consensus, we propose an integer programming model to make both their consistency and consensus better to yield improved FLPRs with acceptable multiplicative consistency and consensus. Furthermore, the DMs' comprehensive weight vector is determined. Then, we propose a new GDM algorithm following the multiplicative consistency and consensus of FLPRs. Finally, the feasibility and the applicability of the proposed GDM method are illustrated via an application example and some comparative analyses with the existing GDM methods. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Acceptable multiplicative consistent Consensus FLPR GDM integer programming model Multiplicative consistency

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Research on task distribution of maritime emergency disposal based on Vogel method

Research on task distribution of maritime emergency disposal...

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第34届中国控制与决策会议

作者： Jiahui Mao Yu Guo Xingliang Wang Yingying Gao Qingqing Yang Kewei Yang National University of Defense Technology College of Systems Engineering

The task distribution of joint emergency disposal for maritime emergencies is an important link to improve the efficiency of joint emergency disposal for maritime emergencies,which involves tasks such as traffic organization,rescue and pollution removal,as well as the close cooperation of multi organizations and social forces such as marine police,maritime affairs,environmental protection and fishery,so as to realize the rapid distribution of tasks,tasks should be reasonably allocated to various organizations to achieve a clear division of *** analyzing the actual process of joint emergency disposal of maritime emergencies,this paper abstracts the problem as an integer programming problem of multi-stage ***,decompose and sort out the joint emergency disposal tasks of maritime emergencies,determine the time sequence relationship between tasks,and construct a multi-stage task network diagram;Then,the organizational task network model is established,and the model implementation idea based on Vogel method is proposed;Finally,an example is calculated based on the scoring data given by the experts who actually participate in the disposal business,and compared with the actual situation of the accident at that *** effectiveness of the model and algorithm in this paper is illustrated by the real "Sangji ship" accident case.

关键词： Joint emergency disposal of maritime emergencies Task distribution Vogel method Task network integer programming model

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Collaborative passenger flow control on an oversaturated metro line: a path choice approach

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Transportmetrica B 2020年第1期8卷 376-404页

作者： Meng, Fanting Yang, Lixing Wei, Yun Li, Shukai Gao, Ziyou Shi, Jungang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China National Engineering Laboratory for Green & Safe Construction Technology in Urban Rail Transit Beijing China College of Transportation and Logistics East China Jiaotong University Nanchang China Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety Tongji University Shanghai China

Focusing on reducing the traffic congestion on an oversaturated urban metro system, this study investigates the collaborative passenger flow control problem for a metro line. By introducing the timetable-oriented space-time network representation, the problem of interest is finally formulated as an integer programming model, in which the objective function aims to minimize the total weighted passenger waiting time at different stations. Since the final decision is closely related to the space-time path-finding process, the proposed model can also be regarded as a coordinated path-finding process with train loading capacity constraints. Then, an efficient heuristic algorithm is developed to solve the proposed model. Finally, a series of numerical examples are implemented on a sample metro line and the Beijing Batong metro line. The computational results show that the proposed approach can produce high-quality passenger flow control strategies for the metro system, thereby demonstrating the effectiveness of the proposed model and algorithm. © 2020, © 2020 Hong Kong Society for Transportation Studies Limited.

关键词： Collaborative passenger control integer programming model lagrangian relaxation approach space-time network

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Additive Consistency of Hesitant Fuzzy Linguistic Preference Relation With a New Expansion Principle for Hesitant Fuzzy Linguistic Term Sets

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2019年第4期27卷 716-730页

Hesitant fuzzy linguistic preference relation (HFLPR) is a new preference structure that the decision makers (DMs) are hesitant about several possible linguistic terms of preference information for pairwise comparison between alternatives. This paper examines the additive consistency of HFLPR with a new expansion principle for hesitant fuzzy linguistic term sets (HFLTSs). In order to normalize HFLTSs with different numbers of linguistic terms, a least common multiple expansion (LCME) principle is proposed. According to the LCME principle, the additive consistent index of an HFLPR is defined to measure the consistency level of the HFLPR. For improving the unacceptable additive consistency of an HFLPR, a pure integer programming model is constructed to derive an acceptable additive consistent HFLPR. In group decision making (GDM) with HFLPRs, the similarities between DMs are calculated based on their individual HFLPR with acceptable additive consistency. Subsequently, the confidence degrees of DMs are defined to derive DMs' weights, and some examples including an investment project management problem are analyzed to verify the effectiveness of the proposed method.

关键词： Additive consistency index group decision making (GDM) hesitant fuzzy linguistic preference relation (HFLPR) integer programming model least common multiple expansion (LCME) principle

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Obstacle-aware optimization of offshore wind farm cable layouts

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ANNALS OF OPERATIONS RESEARCH 2019年第1-2期272卷 373-388页

作者： Klein, Arne Haugland, Dag Univ Bergen Dept Informat Bergen Norway

In this article, an integer linear programming model for cost minimization of cable layouts in offshore wind farms is presented. All turbines must be connected to power substations by cables. Up to a given number, turbines may be connected along a joint cable in a series circuit, and cable branching at turbine locations is possible. No two cables are allowed to cross each other. As an improvement over previously available models, the model under study enables optimal adaptation of the cable routes to obstacles. Obstacles of two different kinds are considered. First, a set of regions in which cables cannot be laid is accepted as part of the input to the model. Second, the trajectory of one cable plays the role of an obstacle to all other cables. Both obstacle types are modeled by introducing optional connection points, which, contrary to the turbines, do not have to be visited by any cable. By introducing such optional connection points at selected positions, we arrive at a model with some resemblance with the Steiner tree problem. We demonstrate that, by virtue of the optional points, the suggested model is able to identify feasible solutions to problem instances where other models fail to do so. In other instances, the model yields more cost-effective cable layouts than previously studied models do. Computational experiments with realistic wind farm instances of up to 88 turbines prove that cabling cost reductions of about 1% are achievable by the model.

关键词： integer programming model Offshore wind farm Cable layout Obstacle avoidance Computational experiments

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Multi-constrained Vehicle Routing Problem Solution based on Adaptive Genetic Algorithm

Multi-constrained Vehicle Routing Problem Solution based on ...

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作者： Wenyu Fan Rutgers Business School Rutgers University–Newark

The Multi-constrained Vehicle Routing Problem(MCVRP) is an extension of the basic vehicle routing problem(VRP). There may be more than one constraint, and the distribution cost is not only related to the routing decision, but also to the transportation volume of vehicles. This paper describes and analyzes the MCVRP, then builds an integer programming model of the multi-constraint vehicle routing problem. For this problem model, the best algorithm for solving multi-constrained vehicle routing problems is based on genetic algorithm(GA). To overcome the shortcomings of traditional GA, an improved adaptive GA for MCVRP optimization is ***, a simulation experiment was performed on the actual data set to verify the effectiveness of the model and algorithm.

关键词： Multi-constrained Vehicle Routing Problem integer programming model adaptive GA

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Determining Server Locations in Server Migration Service to Minimize Monetary Penalty of Dynamic Server Migration

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JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT 2018年第4期26卷 993-1033页

作者： Fukushima, Yukinobu Murase, Tutomu Motoyoshi, Gen Yokohira, Tokumi Suda, Tatsuya Okayama Univ Grad Sch Nat Sci & Technol Kita Ku Tsushimanaka 3-1-1 Okayama Okayama Japan Nagoya Univ Informat Technol Ctr Chikusa Ku Furo Cho Nagoya Aichi Japan NEC Corp Amer 2 Maskit St IL-4673302 Herzliyya Israel Univ Netgrp Inc POB 1288 Fallbrook CA USA

In this paper, we propose a new class of service called server migration service (SMS) to augment the existing IaaS (Infrastructure as a Service). SMS allows servers (server-side processes of a network application) to dynamically and automatically migrate as their clients (client-side processes of a network application) change their locations in order to reduce the total monetary penalty that the SMS provider pays to its SMS subscribers when failing to provide them with the guaranteed level of QoS. In this paper, we consider the monetary impact that arises from QoS degradation due to server migration and build an integer programming model to determine when and to which location servers should migrate to minimize the total monetary penalty incurred by the SMS provider. Numerical examples show that SMS achieves up to 96% lower total monetary penalty compared to that without server migration. Numerical examples also show that the integer programming model developed in this paper requires reasonable computation time under realistic parameter settings.

关键词： Cloud service IaaS Server migration service (SMS) Dynamic and automatic migration Server locations Monetary penalty Service pricing policy integer programming model

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Inventory control model for a supply chain system with multiple types of items and minimum order size requirements

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2018年第6期25卷 1927-1946页

作者： Park, Jun Hyeong Kim, Jong Soo Shin, Ki Young Hanyang Univ Dept Ind & Management Engn Erica Campus Ansan South Korea

This paper considers a replenishment problem for a single buyer who orders multiple types of items from two or more heterogeneous suppliers in order to sell to end customers. The buyer periodically orders each type of item from the suppliers according to a select inventory control policy. Processing the order, each supplier enforces the policy that an order from the buyer must meet a predetermined minimum order quantity (MOQ). Therefore, the buyer must decide how much to order from each supplier considering the current inventory level, demand forecast, and MOQ requirement. The buyer's problem is formulated as an integer programming model and an efficient implementation strategy is suggested to apply the model to real problems. Numerical experiments are performed to test the validity of the proposed model as well as the efficiency of the implementation strategy. The experimental results show that this model combined with the implementation method yields a considerable cost reduction compared to the most efficient policy currently available.

关键词： inventory control minimum order quantity integer programming model

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