物资缺乏情况下的应急物流运输与物资二次分配策略  

Emergency logistics transportation and redistribution strategy in solution of lack of supplies

作　　者：蔡延光[1] 黄戈文[1,2] 黄何列 戚远航 徐云剑 Cai Yanguang;Huang Gewen;Huang Helie;Qi Yuanhang;Xu Yunjian(School of Automation,Guangdong University of Technology,Guangzhou 510006,China;Information&Network Center,Jiaying University,Meizhou Guangdong 514015,China;Guangdong Science&Technology Infrastructure Center,Guangzhou 510033,China;University of Electronic Science&Technology of China,Zhongshan Institute,Zhongshan Guangdong 528402,China;School of Intelligent Engineering,Guangdong AIB Polytechnic,Guangzhou 510507,China)

机构地区：[1]广东工业大学自动化学院,广州510006 [2]嘉应学院信息网络中心,广东梅州514015 [3]广东省科技基础条件平台中心,广州510033 [4]电子科技大学中山学院计算机学院,广东中山528402 [5]广东农工商职业技术学院智能工程学院,广州510507

出　　处：《计算机应用研究》2021年第8期2423-2429,共7页Application Research of Computers

基　　金：国家自然科学基金资助项目(61074147,61901304);广东省自然科学基金资助项目(S2011010005059,2019A1515010493,2016A030313018);广东省教育部产学研结合项目(2012B091000171,2011B090400460);广东省科技计划资助项目(2012B050600028,2014B010118004,2016A050502060);广州市花都区科技计划资助项目(HD14ZD001);广州市科技计划资助项目(201604016055);广州市天河区科技计划资助项目(2018CX005);广东省普通高校青年创新人才项目(2018KQNCX333,2018KQNCX252);广东省普通高校重点领域专项(2019KZDZX1052,2020ZDZX3030)。

摘　　要：针对应急物流中的运输时效性和物资分配公平性问题,提出了一种两阶段应急物流运输与物资二次分配策略。首先,基于所定义的时间满意度、物资满意度和综合满意度,提出了最大时间满意度车辆路径问题模型和最小加权满意度标准差应急物资分配模型。第一阶段针对最大时间满意度车辆路径问题模型设计了一种混合灰狼优化算法进行求解,该算法采用了最优分割过程分组解码策略,并采用了混沌搜索策略、2-Opt和1-1局部搜索策略来提高算法的搜索能力;第二阶段针对最小加权满意度标准差应急物资分配模型设计了混沌灰狼优化算法求解。实验结果表明:在第一阶段,总体时间满意度比CVRP模型提高了39.31%;在第二阶段,当实际物资量为80%和权重系数为0.75时,计算得到的综合满意度标准差为0.0619,物资满意度标准差为0.0974,较好地平衡了灾民的心理诉求和物资利用效能。两阶段应急物流运输与物资二次分配策略得到了较高的时间满意度和较好的物资分配结果,证明了所提模型和算法的有效性。This paper proposed a two-stage emergency logistics transportation and redistribution strategy for the problems considering the transportation timeliness and the supplies distribution fairness in emergency logistics.Firstly,This paper proposed the capacitated vehicle routing problem with maximum time satisfaction(CVRP-MTS)for emergency vehicle transport scheduling and the emergency supplies distribution problem with minimum weighted standard deviation of satisfactions(EMDP-MWSDS)based on the time satisfaction,the supplies satisfaction and the comprehensive satisfaction defined in this paper.Then this paper designed a hybrid grey wolf optimization algorithm(HGWOA)to solve the CVRP-MTS in the first stage.The HGWOA adopted the optimal split procedure decoding strategy,and adopted the chaotic search strategy,the 2-Opt and 1-1 local search strategy to improve the search ability of the algorithm.And this paper implemented the chaotic grey wolf optimization algorithm(CGWOA)to solve the EMDP-MWSDS in the second stage.The experimental results show that in the first stage,overall time satisfaction of the CVRP-MTS is 39.31%higher than that of the CVRP model.In the second stage,when 80%of the actual material quantity and 0.75 for the weight coefficient,the standard deviation of the comprehensive satisfaction degree is 0.0619,and the standard deviation of the supplies satisfaction degree is 0.0974.The distribution results effectively balance the victims’psychological demands and supplies utilization efficiency.The two-stage emergency logistics transportation and supplies redistribution distribution strategy can obtain high time satisfaction and good supplies distribution results,which prove the effectiveness of the proposed models and algorithms.

关 键 词：应急物流 车辆路径问题 物资分配 灰狼优化算法 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]