运筹与管理 ›› 2022, Vol. 31 ›› Issue (9): 7-13.DOI: 10.12005/orms.2022.0278

• 理论分析与方法探讨 • 上一篇    下一篇

考虑需求不确定的多级应急物流设施选址研究

闫森1, 齐金平1,2   

  1. 1.兰州交通大学 机电技术研究所,甘肃 兰州 730070;
    2.甘肃省物流及运输装备信息化工程技术研究中心,甘肃 兰州 730070
  • 收稿日期:2020-08-11 出版日期:2022-09-25 发布日期:2022-10-21
  • 作者简介:闫森(1996-),男,四川简阳人,硕士研究生,主要从事应急物流系统建设等方面的研究;齐金平(1978-),男,山东诸城人, 副教授,博士。从事区域物流服务平台构建研究、区域物流规划、区域生产安全管理体系及平台建设。

Research on Location Selection of Multi-level Emergency Logistics Facilities under Uncertain Conditions

YAN Sen1, QI Jin-ping1,2   

  1. 1. Mechatronics T&R Institute, Lanzhou Jiaotong University, Lanzhou 730070, China;
    2. Engineering Technology Center for Informatization of Logistics & Transport Equipment, Lanzhou 730070, China
  • Received:2020-08-11 Online:2022-09-25 Published:2022-10-21

摘要: 为了对急物流设施选址问题进行合理的研究,建立了包含配送中心、配送点和需求点的多级应急物流网络。基于应急物资需求特点,使用三角模糊数表示应急物资需求的不确定性,同时考虑应急救援成本和应急救援时间两个目标,建立了应急物流设施选址模型。采用去模糊化方法将三角模糊数转化为确定数,利用成本和时间的单目标的最优结果将多目标转化为相对值,再对时间和成本目标进行加权处理,既消除了不同目标之间的单位及数量级差异,还可以进行动态调整。设计了遗传算法对模型进行求解,通过实际算例表明了模型和算法可以有效地解决应急物流设施选址问题。

关键词: 应急物流选址, 多级网络, 多目标优化, 遗传算法, 模糊需求

Abstract: In order to conduct on the location of emergency logistics facilities, a multi-level emergency logistics network including distribution centers, distribution points and demand points is established. Based on the characteristics of the uncertainty of emergency material demand, triangular fuzzy numbers are used to express the uncertainty of emergency material demand, and the emergency rescue cost and time are considered at the same time, and then the location model of emergency logistics facilities is established. The triangular fuzzy number transforms into a certain number by defuzzification method, multiple goals convert into relative values by using the optimal result of the single goal of cost and time, and then time and cost goals are weighted, which eliminates the unit and quantity differences of different targets and can also be adjusted dynamically. A genetic algorithm is designed to solve the model. The actual calculation example shows that the model and algorithm can effectively solve the problem of emergency logistics facility location.

Key words: emergency logistics location, multi-level network, multi-objective optimization, genetic algorithm, fuzzy demand

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