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山东大学学报（理学版） ›› 2018, Vol. 53 ›› Issue (5): 1-11.doi: 10.6040/j.issn.1671-9352.0.2017.294

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复杂风险变量随机模拟下的应急供应调度

何新华1,万帆1,胡文发2,郑爱兵3   

  1. 1. 上海海事大学经济管理学院, 上海 201306;2. 同济大学经济与管理学院, 上海 200092;3.上海财经大学国际工商管理学院, 上海 200433
  • 收稿日期:2017-06-14 出版日期:2018-05-20 发布日期:2018-05-25
  • 作者简介:何新华(1973— ), 女,教授,博士生导师, 研究方向为供应链与物流管理. E-mail:xhhe@shmtu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(71473162,71371145,71102043);上海市科技创新行动计划软科学研究重点项目(17692103900)

Emergency supply scheduling optimization under stochastic simulation of complex risk variables

HE Xin-hua1, WAN Fan1, HU Wen-fa2, ZHENG Ai-bing3   

  1. 1. School of Economics Management, Shanghai Maritime University, Shanghai 201306, China;
    2. School of Economics and Management, Tongji University, Shanghai 200092, China;
    3. School of International Business Administration, Shanghai University of Finance and Economics, Shanghai 200433, China
  • Received:2017-06-14 Online:2018-05-20 Published:2018-05-25

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摘要： 考虑突发事件下的应急资源调度成本和复杂风险变量随机模拟情形,以满足各灾害点的需求最小化调度成本为目标,分析风险变量对运输工具的选择影响而引起的成本变化以及在运输过程中物资损失所引起的费用变化;在一系列模型假设和定义下,构建基于多灾害点的应急供应调度模型,并结合随机模拟与基于细菌趋化的粒子群(particle swarm optimization based on bacterial chemotaxis, PSOBC)基于细菌趋化的粒子群算法进行研究,实现最小化费用成本的目标;最后通过算例分析验证了所建模型和算法是有效和可行的。

关键词: 复杂风险变量, 随机模拟, 基于细菌趋化的粒子群算法, 应急供应调度

Abstract: Considering the cost of emergency resource scheduling in emergencies supply chain, it is necessary to minimize the scheduling cost on the basis of satisfying the demand of each disaster point. This paper considers the changes in costs due to the impact of risk variables on the choice of transportation and the cost changes caused by material losses during transport. Based on a series of model assumptions and definitions, a theoretical model of emergency resource dispatching process based on multi-hazard points was constructed. The problem was solved by the stochastic simulation combined with Particle Swarm Optimization based on Bacterial Chemotaxis(PSOBC)and achieved the minimum cost of the target. Finally, a numerical example was given to demonstrate the effectiveness and feasibility of the proposed model.

Key words: complex risk variables, emergency supply scheduling, stochastic simulation, PSOBC algorithm

中图分类号: 

  • F253
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[1] 何新华,胡文发,许长延,陈继红. 考虑随机性与模糊性的应急服务供应链转运策略[J]. 山东大学学报（理学版）, 2016, 51(12): 67-77.
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