物流运输调度问题的混沌烟花算法——基于多车型供应链  

Chaotic Fireworks Algorithm for Multi-Type Vehicle Routing Problem in Supply Chain

作　　者：蔡延光[1] 戚远航 蔡颢 陈厚仁[1] OLE Hejlesen[2] CAI Yanguang;QI Yuanhang;CAI Hao;CHEN Houren;OLE Hejlesen(School of Automation,Guangdong University of Technology,Guangzhou 510006,China;Department of Health Science&Technology,Aalborg University,Aalborg 9220,Denmark)

机构地区：[1]广东工业大学自动化学院,广州510006 [2]奥尔堡大学健康科学与工程系

出　　处：《计算机工程与应用》2019年第3期238-244,共7页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61074147);广东省自然科学基金(No.S2011010005059);广东省教育部产学研结合项目(No.2012B091000171;No.2011B090400460);广东省科技计划项目(No.2012B050600028;No.2014B010118004;No.2016A050502060);广州市花都区科技计划项目(No.HD14ZD001);广州市科技计划项目(No.201604016055)

摘　　要：为了满足供应链物流的不同需求,考虑多种车型、车辆容量、车辆油耗、车辆最大配送距离等约束条件,以最小油耗、最短配送距离为目标,建立多车型供应链物流运输调度模型(Multi-Type Vehicle Routing Problem in Supply Chain,MTVRPSC),并提出一种混沌烟花算法求解该模型。该算法以烟花算法为核心,提出一种编解码策略实现连续空间到MTVRPSC离散空间的映射,重新定义算法的适应度函数、适应度值和适应度的比较方法,并采用混沌初始化策略和混沌搜索策略来增强算法收敛效果。实验结果表明,所提出的算法在求解MTVRPSC时具有较强的寻优能力和稳定性。In order to satisfy the demands of supply chain logistics,considering with multi-type vehicles,capacity of the vehicle,fuel consumption of the vehicle,maximum delivery distance of vehicle,and aiming to minimize the fuel consumption and delivery distance,the paper constructs a model of Multi-Type Vehicle Routing Problem in Supply Chain(MTVRPSC)and proposes a chaotic fireworks algorithm to solve it.The proposed algorithm takes the fireworks algorithm as the core,and proposes a codec strategy to accomplish a mapping from the continuous space to the discrete space of MTVRPSC,and redefines the fitness function,fitness value and comparative approach of fitness.The proposed algorithm also adopts the chaotic initialization strategy and chaotic search strategy to enhance the convergent effect.Experimental results show that,the proposed algorithm has the strong optimization ability and stability to solve MTVRPSC.

关 键 词：烟花算法 混沌优化算法 供应链 车辆路径问题 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]