首页> 外文期刊>Fuzzy Optimization and Decision Making >A multi-objective chance-constrained network optimal model with random fuzzy coefficients and its application to logistics distribution center location problem
【24h】

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

机译:随机模糊系数的多目标机会约束网络最优模型及其在物流配送中心选址中的应用

获取原文
获取原文并翻译 | 示例
       

摘要

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.
机译:配送中心的问题涉及如何从潜在的集合中选择配送中心,以使包括配送中心的固定成本和运输成本在内的总相关成本最小化,并使运输时间最小化。本文针对物流配送中心选址问题,提出了一种具有随机模糊系数的多目标网络最优模型。此外,我们通过概率和可能性度量将不确定模型转换为确定性模型。然后引入了基于Prüfer数表示法的基于生成树的遗传算法(st-GA),以解决清晰的多目标规划问题。最后,将提出的模型和算法应用于新溪乳业控股有限公司,以证明其有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号