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A multi-objective chance-constrained network optimal model with random fuzzy coefficients and its application to logistics distribution center location problem

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Abstract

The problem of the distribution center is concerned with how to select distribution centers from a potential set in order to minimize the total relevant cost comprising of fixed costs of the distribution center and transport costs, and minimize the transportation time. In this paper, we propose a multi-objective network optimal model with random fuzzy coefficients for the logistics distribution center location problem. Furthermore, we convert the uncertain model into a deterministic one by the probability and possibility measure. Then the spanning tree-based genetic algorithm (st-GA) by the Prüfer number representation is introduced to solve the crisp multiobjective programming. At last, the proposed model and algorithm are applied to the Xinxi Dairy Holdings Limited Company to show the efficiency.

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Authors and Affiliations

  1. Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu, 610064, People’s Republic of China

    Jiuping Xu, Liming Yao & Xiaodan Zhao

Authors
  1. Jiuping Xu
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  2. Liming Yao
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  3. Xiaodan Zhao
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Correspondence to Jiuping Xu.

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Xu, J., Yao, L. & Zhao, X. A multi-objective chance-constrained network optimal model with random fuzzy coefficients and its application to logistics distribution center location problem. Fuzzy Optim Decis Making 10, 255–285 (2011). https://doi.org/10.1007/s10700-011-9105-6

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