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The Optimization Approach for Traffic Rescue Resource Dispatch on Expressway Based on fuzzy programming

5th Annual Conference on fuzzy Information and Engineering

作者： Zhu, Canghui Li, Xinghua Chai, Gan Transport Planning & Res Inst Minist Transport Beijing 100028 Peoples R China Southeast Univ Transportat Coll Nanjing 210096 Peoples R China

ISBN: (纸本)9783642148798

In order to reveal the uncertainty in the process of rescuing the accidents over the expressway network, fuzzy programming method is used to establish the rescue resource dispatch model. The model aims to minimize the fuzzy dispatch decision-making time to reflect the accidents' influence on the upper traffic flow after accidents happen on the fully-closed expressway. fuzzy chance constraint is designed to reflect the relationship between the uncertain requirements of potential accidents and the existing resource allocation. According to the limitation of the traditional algorithm and the complexity of dispatch problems, especially many accidents happening simultaneously and various rescue resources required, the genetic algorithm based on fuzzy simulation is designed to be fit for the model and the optimized dispatch scheme is obtained. The case study of the expressway network in Henan Province is conducted to illustrate that the fuzzy dispatch method can be used to solve the conflicts between shortening the decision-making time and reducing the rescuing economic costs compared with the existing rescue mode, and the optimum rescue resource dispatch decision is made for the command control center.

关键词： fuzzy programming expressway traffic rescue resource genetic algorithm optimized dispatch approach

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fuzzy programming and Multi-Objectives Evaluation Model in the Supplier Relationship Management

Fuzzy Programming and Multi-Objectives Evaluation Model in t...

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第三届IEEE无线通讯、网络技术暨移动计算国际会议

作者： Xiaobei Liang Bingyong Tang School of Management Tongji University Shanghai 200092 China Glorious Sun School of Business and Management Dong Hua University P.R.China 200051

In this paper, the fuzzy variation coefficients programming is discussed, and the multi-objectives evaluation method is put forward in the supplier relationship management, the major thoughts are: First choosing n different suppliers evaluation criterion to be a ndimensions space, every suppliers information is a point this space, then we can calculate the Euclid distance between these points and the best or worst point. Finally we sort the suppliers by the distance.

关键词： fuzzy programming multi-objectives evaluation supplier relationship management

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fuzzy programming model and algorithm for optimal design of distribution centers for B2C e-commerce

Fuzzy programming model and algorithm for optimal design of ...

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2007 IEEE International Conference on Automation and Lofistics

作者： Zhongzhong Jiang Dingwei Wang W.H. Ip School of Business Administration Northeastern University Shenyang P.R.China School of Information Science and Engineering Northeastern University Shenyang P.R.China Department of Industrial and Systems Engineering Hong Kong Polytechnic University Hong Kong P.R.Chi

With respect to the customer characteristics of little demand, multi-commodity, and dispersed location, a fuzzy programming model is proposed to optimize the design of distribution centers for business-to-consumer (B2C) e-commerce, in which a hierarchical agglomerative clustering method is introduced to classify customers and estimate the unit weight fuzzy delivery cost from distribution centers to customers. Both commodity supplies and customer demands in the whole plan period are treated as fuzzy numbers. The model is nonlinear because of the scale-economy effect. Therefore, it is not easy to obtain the optimal solution with conventional methods. The problem is solved firstly, by converting it into a crisp model, followed by the implementation of a genetic algorithm with particle swarm optimization. The computational results on simulative examples have demonstrated the effectiveness and feasibility of the model and algorithm.

关键词： E-commerce distribution centers fuzzy programming particle swarm optimization genetic algorithm

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A fuzzy programming model for optimizing the inventory management problem considering financial issues: A case study of the dairy industry

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EXPERT SYSTEMS WITH APPLICATIONS 2023年 221卷

作者： Taheri, Mona Amalnick, Mohsen Sadegh Taleizadeh, Ata Allah Mardan, Ehsan Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Semnan Univ Dept Ind Engn Semnan Iran

In today's competitive environment as well as the dynamic nature of the business environment, managing in-ventory and financial flows has become more challenging. As inventory and financial flows are interdependent, setting an optimal plan for managing them simultaneously can have a dramatic impact on the company's effi-ciency The literature indicates that previous studies have rarely considered financial considerations in the in-ventory management problem. Thus, this study proposes a multi-objective programming model to optimize the inventory management problem for dairy products. In the model, material substitution is considered in order to assist in managing the inventory value. A fuzzy model is developed to deal with uncertain parameters such as inventory costs, raw milk volume, and the cost of purchasing raw materials. Then, a real-world case study is conducted in the Iranian dairy industry. Additionally, the proposed model is solved using a multi-choice goal programming approach. Further, sensitivity analyses are conducted in order to investigate the impact of critical parameters on the research question. Finally, managerial insights and theoretical implications are discussed. Based on the results, raw milk volume decreases inventory costs, and material substitution decreases inventory value as obsolete materials are used in products.

关键词： Inventory management Financial issues fuzzy programming Multi-choice goal programming

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Designing and planning the downstream oil supply chain under uncertainty using a fuzzy programming approach

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COMPUTERS & CHEMICAL ENGINEERING 2021年 151卷 107373-107373页

作者： Lima, Camilo Relvas, Susana Barbosa-Povoa, Ana Escola Super Naut Infante D Henrique ENIDH Av Engenheiro Bonneville Franco P-2770058 Paco De Arcos Portugal Univ Lisbon Inst Super Tecn CEG IST Av Rovisco Pais P-1049001 Lisbon Portugal

This paper addresses the strategic and tactical planning of a downstream oil supply chain (DOSC) subject to different sources of uncertainty. This problem is formulated as a mixed-integer linear programming (MILP) model, whereas uncertainty is tackled using chance constrained programming with fuzzy param-eters. The MILP model aims at determining the network design and the products distribution plan in a cost-effective way. A real case study on the Brazilian oil industry is used to validate the model. The pro-posed model shows to be a valuable decision-support tool in order to aid the decision-making process in the strategic and tactical planning of real-life problems. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Strategic and tactical planning Downstream oil supply chain Optimization fuzzy programming Uncertainty

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Interactive fuzzy programming for two-level 0-1 programming problems with fuzzy parameters through genetic algorithms

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ELECTRONICS AND COMMUNICATIONS IN JAPAN PART III-FUNDAMENTAL ELECTRONIC SCIENCE 2000年第6期83卷 40-49页

作者： Sakawa, M Nishizaki, I Hitaka, M Hiroshima Univ Fac Engn Higashihiroshima 7398527 Japan

In this paper, an interactive fuzzy programming method using genetic algorithms has been proposed for two-level 0-1 programming problems with fuzzy parameters. According to the proposed technique, the decision maker in each level establishes his fuzzy goals related to the objective functions, using linear membership functions. After that, the upper level decision maker establishes, subjectively, the minimal acceptable degree of the degree of satisfaction for the membership functions and, simultaneously, considers the ratio of satisfaction degrees between the levels;if necessary, the decision maker updates his minimal acceptability degree interactively. In so doing, a satisfactory solution is produced by taking into consideration also the achievement balance of the overall satisfaction degree, while respecting the upper-level decision maker's decision. The feasibility and validity of the proposed method was demonstrated through a numerical example for a two-level 0-1 programming problem with fuzzy parameters. The algorithm proposed in this paper can be extended to multilevel problems. (C) 2000 Scripta Technica.

关键词： two-level 0-1 programming problem fuzzy programming fuzzy objective genetic algorithm interactive method

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An Efficient fuzzy programming Approach for the Vehicle Routing Problem with Soft Time Windows

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JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING 2014年第4-6期22卷 443-457页

作者： Kilic, Sezgin Kaplan, Sezgin Turkish Air Force Acad Dept Ind Engn TR-34149 Istanbul Turkey

This paper considers the vehicle routing problem with soft time windows (VRPSTW) where the customers' preferences and tolerances on the latest delivery times are handled by use of a fuzzy programming model. The proposed model and the solution approach make easy to trade-off distributors' various strategies between efficiency and responsiveness spectrum. An indirect enumeration strategy is proposed to generate all pseudo-dominant (Pareto) solutions to the VRPSTW. A simulated annealing (SA) algorithm is implemented to solve the test problems. The importance and advantages of the proposed approach are illustrated by numerical results.

关键词： Vehicle routing problem soft time windows fuzzy sets simulated annealing fuzzy programming

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How Uncertain Information on Service Capacity Influences the Intermodal Routing Decision: A fuzzy programming Perspective

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INFORMATION 2018年第1期9卷 24页

作者： Sun, Yan Zhang, Guijie Hong, Zhijuan Dong, Kunxiang Shandong Univ Finance & Econ Sch Management Sci & Engn 7366 Second Ring East Rd Jinan 250014 Shandong Peoples R China

Capacity uncertainty is a common issue in the transportation planning field. However, few studies discuss the intermodal routing problem with service capacity uncertainty. Based on our previous study on the intermodal routing under deterministic capacity consideration, we systematically explore how service capacity uncertainty influences the intermodal routing decision. First of all, we adopt trapezoidal fuzzy numbers to describe the uncertain information of the service capacity, and further transform the deterministic capacity constraint into a fuzzy chance constraint based on fuzzy credibility measure. We then integrate such fuzzy chance constraint into the mixed-integer linear programming (MILP) model proposed in our previous study to develop a fuzzy chance-constrained programming model. To enable the improved model to be effectively programmed in the standard mathematical programming software and solved by exact solution algorithms, a crisp equivalent linear reformulation of the fuzzy chance constraint is generated. Finally, we modify the empirical case presented in our previous study by replacing the deterministic service capacities with trapezoidal fuzzy ones. Using the modified empirical case, we utilize sensitivity analysis and fuzzy simulation to analyze the influence of service capacity uncertainty on the intermodal routing decision, and summarize some interesting insights that are helpful for decision makers.

关键词： intermodal transportation routing decision capacity uncertainty fuzzy programming

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A method for solving fuzzy goal programming problems based on MINMAX approach

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第3期177卷 1580-1590页

作者： Yaghoobi, M. A. Tamiz, M. Univ Portsmouth Dept Math Portsmouth PO1 3HE Hants England Univ Kerman Fac Math & Comp Sci Kerman Iran

Narasimhan incorporated fuzzy set theory within goal programming formulation in 1980. Since then numerous research has been carried out in this field. One of the well-known models for solving fuzzy goal programming problems was proposed by Hannan in 1981. In this paper the conventional MINMAX approach in goal programming is applied to solve fuzzy goal programming problems. It is proved that the proposed model is an extension to Hannan model that deals with unbalanced triangular linear membership functions. In addition, it is shown that the new model is equivalent to a model proposed in 1991 by Yang et al. Moreover, a weighted model of the new approach is introduced and is compared with Kim and Whang's model presented in 1998. A numerical example is given to demonstrate the validity and strengths of the new models. (c) 2005 Elsevier B.V. All rights reserved.

关键词： fuzzy goal programming goal programming fuzzy programming MINMAX approach

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A note on "Generalized fuzzy linear programming for decision making under uncertainty: Feasibility of fuzzy solutions and solving approach"

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INFORMATION SCIENCES 2014年 266卷 226-227页

作者： Kumar, Amit Appadoo, S. S. Bector, C. R. Thapar Univ Sch Math & Comp Applicat Patiala Punjab India Univ Manitoba Asper Sch Business Dept Supply Chain Management Winnipeg MB R3T 2N2 Canada Univ Manitoba Asper Sch Business Dept Business Adm Winnipeg MB R3T 2N2 Canada

关键词： Decision making fuzzy programming fuzzy solution

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