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Mathematical modeling and simulated annealing algorithm for spatial layout problem

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第3-Sup期22卷 S6383-S6391页

作者： Jiang, Liupeng Ji, Jie Lu, Yuhua Chen, Yanan Jia, Yue Hohai Univ Coll Harbour Coastal & Offshore Engn Nanjing Jiangsu Peoples R China

The spatial layout of the port industrial zone problem is a core issue in port industrial zone planning, and it directly affects the actual effects of the port industrial zone. Firstly, considering that existing port industrial zone planning lacks in methods of quantitative analysis, this paper constructs a Mathematical model based on multi-objective programming, and the optimal scale of various industries of port industrial zone is obtained. Secondly, the paper takes the maximum dependence degree of port as objective function by using systematic layout planning tools, and solves the spatial layout of the port industrial zone. Finally, by taking Binhai Port industrial zone of China as an example, a port industrial zone spatial layout model is constructed and solved through simulated annealing algorithm. The optimal spatial layout program for Binhai Port industrial zone of China was obtained, which verifies the feasibility and accuracy of the model.

关键词： Port industrial zone Spatial layout multi-objective programming Systematic layout planning Simulated annealing algorithm

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System portfolio selection with decision-making preference baseline value for system of systems construction

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EXPERT SYSTEMS WITH APPLICATIONS 2019年 123卷 345-356页

作者： Dou, Yajie Zhou, Zhexuan Xu, Xiangqian Lu, Yanjing Natl Univ Def Technol Coll Syst Engn Changsha 410073 Hunan Peoples R China Inst Logist Sci & Technol 2 Feng Ti South Rd Beijing 100071 Peoples R China

For multi-objective problems, most corresponding methods will terminate when the non-dominated set (Pareto set) is acquired, while some redundant systems may exist in it. The same situation may appear in the weapon system portfolio selection as it always tends to be a multi-objective problem. The paper employs a baseline-based method to decide whether to select a redundant system. First, the problem is analyzed in depth to demonstrate the connotation of baseline and related concepts are defined. Then, based on the definition of the redundancy system, baseline system, and baseline value, the weapon system portfolio selection approach with regard to a baseline value is proposed. Starting from the two core parts of the approach, selection strategy analysis, and weapon systems ranking, the strategy analysis of weapon system selection under a single objective and multiple objectives were performed. Subsequently, the interval number theory was employed to extend the VIKOR method to the E-VIKOR method, with a linear programming model as the weighting method under uncertainties to rank the candidate weapon systems. Finally, a case with three different ranking results of candidate weapon systems are studied under different weighting schemes. Based on the ranking results, baseline value, and selection strategy, the weapon system portfolio refining was developed. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Weapon system portfolio selection (WSPS) MCDM Preference baseline value multi-objective programming Interval-number

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Solving the multi-criteria time-dependent routing and scheduling problem in a multimodal fixed scheduled network

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2009年第1期192卷 18-28页

作者： Androutsopoulos, Konstantinos N. Zografos, Konstantincis G. Athens Univ Econ & Business Transportat Syst & Logist Lab Dept Management Sci & Technol Athens 11362 Greece

multi-criteria routing and scheduling in a multimodal fixed scheduled network with time-dependent travel times involves the determination of the non-dominated itineraries (i.e., paths enhanced with scheduled departures) under the following constraints: (i) visiting a given set of intermediate stops in a specified sequence, and (ii) strict time windows on the origin, the destination and the intermediate stops. The objective of this paper is to present the formulation and algorithmic solution for the multi-criteria itinerary planning problem that takes into account the aforementioned features. The algorithmic approach proposed is based on the decomposition of the problem to a sequence of elementary itinerary sub-problems, solved by a dynamic programming algorithm. The computational performance of the algorithms on a set of large scale test problems indicates non-prohibitive time requirements and encourages its integration into travel planning decision support systems. (C) 2007 Elsevier B.V. All rights reserved.

关键词： (B) Routing multi-objective programming Dynamic programming

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A robust optimization model for efficient and green supply chain planning with postponement strategy

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2019年第0期214卷 266-283页

作者： Jabbarzadeh, Armin Haughton, Michael Pourmehdi, Fahime Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Wilfrid Laurier Univ Lazaridis Sch Business & Econ 64 Univ Ave West Waterloo ON N2L 3C7 Canada ETS Dept Automated Prod Engn Montreal PQ Canada

This paper presents a bi-objective robust optimization model for the integrated production and distribution planning of a supply chain with the postponement strategy. The two objectives are economic (cost minimization) and environmental (greenhouse gas emissions minimization), respectively. The robust model is capable of incorporating decision makers' risk attitudes in addressing demand uncertainties under conditions of very limited historical data. The application of the proposed approach is examined using real data of an actual pharmaceutical supply chain as well as a benchmark problem in the existing literature. Our analysis and investigation focuses on exploring the extent to which the tradeoffs between economic and environmental objectives are influenced by the decision makers' risk preferences and postponement strategy. We find that independent of the amount of greenhouse gas emissions and degree of demand variability, the postponement strategy can consistently provide cost savings for the supply chain.

关键词： Supply chain Production-distribution planning Postponement strategy Robust optimization Sustainability Uncertainty multi-objective programming

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Examining the potential of an irrigation work to improve sustainability in a rural area

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WATER SUPPLY 2021年第6期21卷 2959-2973页

作者： Ragkos, Athanasios Ambas, Vasileios Hellen Agr Org DIMITRA Agr Econ Res Inst Athens 11528 Greece Univ Western Macedonia Sch Agr Terma Kontopoulou 53100 Florina Greece

Irrigation works aim to increase the efficiency of water use and economic benefits for farmers. This study adopts a broader view and investigates their potential to contribute to the achievement of other sustainability objectives. In particular, the paper employs a multi-objective programming (MOP) model, which examines the possibilities to simultaneously achieve four conflicting objectives with the upgrade of an irrigation network in a rural area in Greece. The four objectives are maximization of economic result (economic sustainability) and of employment (social sustainability) as well as the minimization of agrochemical use and irrigation water consumption (environmental sustainability). The compromise is sought through different cropping patterns either by restructuring existing crops (Scenario 1) or by also introducing new crops (Scenario 2). The results show that solutions in Scenario 2 performs much better in all dimensions of sustainability, however large increases in economic performance and employment come with lower environmental gains. A Cost-Benefit Analysis shows that very few solutions yield positive Net Present Value and the investment could be halted if benefits relating to social and environmental sustainability are disregarded. Results are discussed in conjunction to the proposal of a new governance scheme, which could assume broader roles in supporting sustainable development.

关键词： cost-benefit analysis crop restructuring governance multi-objective programming public-private partnerships technical and economic data

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OPTIMIZATION OF A LINEAR FUNCTION OVER AN INTEGER EFFICIENT SET

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2023年第12期19卷 8633-8656页

作者： Pherna Sharma, Vikas Thapar Inst Engn & Technol Sch Math Patiala India

Optimizing a function over an efficient set is an interesting approach in decision-making situations. It helps a decision-maker to discriminate among efficient solutions and choose his preferred solution. In this paper, ranked solutions of an integer linear programming problem are utilized for optimizing a linear function over an efficient set of a multi-objective integer linear programming problem (MOILP). For enumerating ranked solutions of an integer linear programming problem, successive optimization of an integer linear programming problem is used. Theoretically, we have shown that the proposed algorithms optimize a linear function over an efficient set of a MOILP in a finite number of iterations. We have compared the working of proposed algorithms with existing algorithms using a numerical example taken from the literature. We have also included a comparison with existing methods based on computational experiments using large number of variables and objectives.

关键词： multi-objective programming integer programming efficient set

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multi-objective modeling for determining location of undesirable facilities

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TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT 2004年第2期9卷 125-138页

作者： Rakas, J Teodorovic, D Kim, T Univ Calif Berkeley Inst Transportat Studies Natl Ctr Excellence Aviat Operat Res Berkeley CA 94720 USA Virginia Polytech Inst & State Univ No Virginia Ctr Charles E Via Jr Dept Civil & Environm Engn Falls Church VA 22043 USA Univ Maryland Dept Civil & Environm Engn College Pk MD 20742 USA

This paper develops a model for determining locations of undesirable facilities. It is formulated as multiobjective since the problem of locating undesirable facilities faces many conflicting criteria. A method is also proposed to appropriately address uncertainty associated with this class of location problems. The methodology developed in this study is tested using the real-world data. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： fuzzy linear programming location multi-objective programming optimization undesirable facilities

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Power Saving Bandwidth Allocation over GEO Satellite Networks

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IEEE COMMUNICATIONS LETTERS 2012年第5期16卷 596-599页

作者： Bisio, Igor Marchese, Mario Univ Genoa DYNATECH Dept Genoa Italy

The problem of bandwidth allocation may be simply stated, independently of the target of the allocation: an amount of bandwidth must be shared among different entities. Each entity receives a portion of the overall bandwidth. Bandwidth allocation may be formalized as a multi-objective programming (MOP) problem where the constraint is the maximum available bandwidth. The objectives of the allocation such as loss and power may be modelled through a group of objective functions possibly contrasting with each other. It is quite intuitive that using more bandwidth will reduce losses, but also that transmitted power will increase with the bandwidth. Which is the balance among these needs? This letter proposes an extended model for bandwidth allocation and uses a modified version of a MOP-based bandwidth allocation [1] to provide a possible solution to the mentioned balancing problems.

关键词： Bandwidth allocation multi-objective programming power and bandwidth saving satellite communications

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Compounding problem in an interactive multiple objective optimization method

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2016年第3期248卷 1132-1135页

作者： Park, K. Sam Lee, Pyoungsoo Korea Univ Sch Business Seoul 136701 South Korea

This note finds and resolves a compounding problem in the interactive multi-objective optimization method developed by Park and Shin (2012). The compounding problem means that the algorithm generates a solution unexpected by the decision maker. A concrete example of the compounding problem is demonstrated and, to remove the problem, an improved algorithm is then developed. We also show that the improved algorithm converges to the known optimal solutions faster than the earlier algorithm. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.

关键词： multi-objective programming Interactive method Compounding problem

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Modeling target volume flows in forest harvest scheduling subject to maximum area restrictions

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TOP 2014年第1期22卷 343-362页

作者： Martins, Isabel Ye, Mujing Constantino, Miguel Fonseca, Maria da Conceicao Cadima, Jorge Inst Super Agron Dept Ciencias & Engn Biosistemas P-1349017 Lisbon Portugal Northwestern Univ Evanston IL 60208 USA Ctr Invest Operac Fac Ciencias Lisboa Dept Estat & Invest Operac P-1749016 Lisbon Portugal

In forest harvest scheduling problems, one must decide which stands to harvest in each period during a planning horizon. A typical requirement in these problems is a steady flow of harvested timber, mainly to ensure that the industry is able to continue operating with similar levels of machine and labor utilizations. The integer programming approaches described use the so-called volume constraints to impose such a steady yield. These constraints do not directly impose a limit on the global deviation of the volume harvested over the planning horizon or use pre-defined target harvest levels. Addressing volume constraints generally increases the difficulty of solving the integer programming formulations, in particular those proposed for the area restriction model approach. In this paper, we present a new type of volume constraint as well as a multi-objective programming approach to achieve an even flow of timber. We compare the main basic approaches from a computational perspective. The new volume constraints seem to more explicitly control the global deviation of the harvested volume, while the multi-objective approach tends to provide the best profits for a given dispersion of the timber flow. Neither approach substantially changed the computational times involved.

关键词： Forest harvest scheduling Area restriction model Volume constraint Integer programming multi-objective programming

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