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考虑车辆等待的应急物资调配方案优化研究
引用本文:宋英华,葛艳,杜丽敬,吕伟.考虑车辆等待的应急物资调配方案优化研究[J].控制与决策,2019,34(10):2229-2236.
作者姓名:宋英华  葛艳  杜丽敬  吕伟
作者单位:武汉理工大学管理学院,武汉,430070;武汉理工大学管理学院,武汉,430070;武汉理工大学管理学院,武汉,430070;武汉理工大学管理学院,武汉,430070
基金项目:国家重点研发计划项目(2016YFC0802500);国家自然科学基金项目(51604204,71501151);国家社会科学基金项目(16CTQ022);中央高校基本科研业务费专项资金项目(2016VI003).
摘    要:为了提高应急救援效率,结合震后灾民对应急物资的需求特征以及应急物资进行两级调配的特点,提出一种考虑应急车辆在应急配送中心等待情况的多物资、多级配送的应急物资调配方案优化模型.结合所研究模型的特征,提出利用基于实数编码的遗传算法对模型进行求解,并依据具体算例将所提出的考虑已到达配送中心处的应急车辆是否需要等到下批应急物资运达该地后再开始下级配送的新决策方式与两种传统方式进行比较分析,验证所提出模型的有效性和可行性.结果表明:所提出的优化模型结合了两种传统方式的优点,在提高灾民对运达应急物资的数量及时间的综合满意度的同时,降低了运输费用.

关 键 词:遗传算法  实数编码  多目标优化  应急物资调配  满意度  方案优化

Optimization of emergency materials allocation plan considering vehicle waiting
SONG Ying-hu,GE Yan,DU Li-jing and LYU Wei.Optimization of emergency materials allocation plan considering vehicle waiting[J].Control and Decision,2019,34(10):2229-2236.
Authors:SONG Ying-hu  GE Yan  DU Li-jing and LYU Wei
Affiliation:School of Management,Wuhan University of Technology,Wuhan430070,China,School of Management,Wuhan University of Technology,Wuhan430070,China,School of Management,Wuhan University of Technology,Wuhan430070,China and School of Management,Wuhan University of Technology,Wuhan430070,China
Abstract:In order to improve the efficiency of emergency rescue, considering the characteristics of the two-level deployment of emergency materials and the demand of victims, this paper proposes an optimization model for emergency materials allocation scheme considering multi-material and multi-level distribution of emergency vehicles in the emergency distribution center. Combining the characteristics of the research model, the genetic algorithm based on real coding is developed to solve the model. A specific example is provided to analyze whether the emergency vehicle that has reached the distribution center needs to wait until the next batch of emergency materials arrives or not. This new decision-making method is compared with two traditional methods to verify the validity and feasibility of the model. The results show that the proposed optimization model combines the advantages of the two traditional methods, and reduces the transportation costs while improving the overall satisfaction of the victims on the amount and time of delivery of emergency materials.
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