交通运输系统工程与信息

交通运输系统工程与信息 ›› 2014, Vol. 14 ›› Issue (4): 160-167.

• 系统工程理论与方法 • 上一篇    下一篇

应急物资保障系统模糊多目标LARP 研究

陈刚a,b，张锦*a,b，付江月a,b   

  1. 西南交通大学a.交通运输与物流学院；b.综合交通运输智能化国家地方联合工程实验室，成都610031
  • 收稿日期:2013-10-26 修回日期:2014-02-18 出版日期:2014-08-25 发布日期:2014-09-16
  • 作者简介:陈刚（1987-），男，四川岳池人，博士生.
  • 基金资助:

    国家社会科学基金资助项目(11BJL054).

Multi-objective Fuzzy Location-allocation-routing Problem in Urgent Relief Distribution System

CHEN Ganga,b, ZHANG Jina,b, FU Jiang-yuea,b   

  1. a. School of Transportation and Logistics; b. National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu 610031, China
  • Received:2013-10-26 Revised:2014-02-18 Online:2014-08-25 Published:2014-09-16

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被引次数

16

摘要：

为了将应急物资快速有效地配送至灾区，从供应链的角度构建一个包含应急 物资供应点、集散点、配送中心及受灾点四层结构的应急物资保障系统. 在考虑需求不确 定性的基础上建立一个双层优化模型. 上层模型以最晚运达时间最小、配送总成本最小 及车辆载重利用率最大为目标，决策灾区应急物资配送中心的选址及车辆路径安排；下 层模型以运输总成本最小为目标，决策应急物资集散点的选址及应急物资的分配. 设计 一种自适应遗传算法求解上层模型，运用GAMS 软件求解下层模型. 以“4· 20”四川芦山 地震应急物资保障为背景构建算例，验证模型和算法的可行性和有效性.

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关键词: 物流工程, 多目标优化, 自适应遗传算法, 选址-分配-路径问题, 模糊需求

Abstract:

To distribute the urgent relief commodities to the disaster areas with high efficiency, this study proposes a four-layer urgent relief distribution system consisting supply depots, transshipment depots, distribution centers and affected areas, from the perspective of supply chain. A bi-level optimization model is proposed with consideration of the uncertain demand. The location of distribution centers and the route scheduling of delivery vehicles are determined by the upper model with the goals of minimizing the last arrival time and the total delivery cost, as well as maximizing the vehicle load utilization. The location of transshipment depots and allocation of relief commodities are decided by the lower model with the goal of minimizing the total transportation cost. A self-adaptive genetic algorithm is also proposed to solve the upper model, and the GAMS is employed to solve the lower model. A numerical example of“4· 20”Sichuan Lushan earthquake of China is presented to verify the feasibility and effectiveness of the model and algorithm.

Key words: logistics engineering, multi-objective optimization, self-adaptive genetic algorithm, locationallocation- routing problem, fuzzy demand

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