工业工程

工业工程

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基于灰色聚类评估的配送中心选址模糊多目标优化模型

  

  1. 重庆工商大学 1. 重庆市发展信息管理工程技术研究中心; 2.电子商务及供应链系统重庆市重点实验室，重庆 400067
  • 出版日期:2016-10-31 发布日期:2017-02-21
  • 作者简介:李志(1965-)，男，重庆市人，教授，硕士，主要研究方向为物流系统规划、物流信息化与供应链管理.
  • 基金资助:

    教育部人文社会科学研究资助项目(15XJC630009); 重庆市教委科学技术研究资助项目(KJ1500603); 重庆工商大学科研启动经费资助项目(2015-56-10); 重庆工商大学校内科研资助项目(670101548);重庆市发展信息管理工程技术研究中心开放基金资助项目(gczxkf201602)

A Fuzzy Multi-objective Optimization Model for Distribution Center Location Based on Grey Clustering Evaluation

  1. 1. Chongqing Engineering Technology Research Center for Information Management in Development, Chongqing Technology and Business University, Chongqing 400067, China; 2. Chongqing Key Laboratory of Electronic Commerce & Supply Chain System, Chongqing Technology and Business University, Chongqing 400067, China
  • Online:2016-10-31 Published:2017-02-21

摘要： 将多属性决策方法与最优化方法相集成，研究了多配送中心选址优化问题。首先采用灰色聚类决策计算各候选地定性属性的综合评估值。再以选定配送中心的评估值均值最大化、系统成本最小化，以及配送中心容量利用率最大化作为3个优化目标，建立一个考虑需求点模糊需求、供应点与候选配送中心容量限制的三级供应链系统多配送中心选址模型。该模型被描述成了一个多目标的非线性混合整数规划模型。采用机会约束规划对模糊需求进行清晰化处理，并应用目标加权的方法将问题转化为单目标问题。通过算例验证了所提模型的可行性。在实际工作中，可根据决策者权重偏好得出令人满意的结果。

关键词: 配送中心, 选址, 灰色聚类评估, 多目标优化模型

Abstract:

A logistics system has distribution centers as its key nodes, and the rationality of distribution centers location decision is of great value. The location of multidistribution centers is studied integrating multiattribute decision making method and optimization method. Firstly, the candidate locations are evaluated based on grey clustering decision. Then, three objective functions are considered as follows, to minimize the total logistics cost, to maximize the capacity utilization and mean evaluating scores of open distribution centers. Besides, a distribution center location model in three echelon supply chain system is built considering fuzzy demands and capacity constraints. This model is depicted as a mixed integer nonlinear programming model. Using chance constrained programming to clear the fuzzy demand, the problem is transformed into a single objective problem based on target weighting. Lastly, a numerical example is given to verify the feasibility of the proposed model. In reliability, satisfactory results can be obtained according to the weight preference of the decision makers.

Key words: distribution center, location, grey clustering evaluation, multiobjective optimization model