摘要
【目的】在改进动态惯性权重粒子群算法的基础上,结合VNS算法,进一步改善该算法的局部搜索能力和全局寻优能力。【方法】以配送质押物的车辆运行总距离最小为目标,将它转化为带距离和容量约束的车辆路径问题,建立数学模型。针对粒子群算法的优缺点,设计用于求解该问题的混合变邻域搜索粒子群算法。【结果】利用该算法求解应用实例,与基本粒子群算法对比求解的算法收敛过程和所得配送路径方案。【结论】通过实例研究表明,所改进的算法能够快速跳出局部收敛,全局寻优能力得到改善,且收敛速度更快,能够较好地为质押物配送路径问题提供解决方案。
[Purposes]The delivery of collateral is a crucial operational process in inventory financing.Optimization of collateral delivery path can save delivery time,reduce collateral risk in transit and retrench transport costs.[Methods]Against this background,the capacitated vehicle routing problem is studied with distance constraints（DCVRP）consisting in deriving the most favorable vehicle pathways that minimize the vehicles＇ traveled distances subject to system requirements.To tackle the DCVRP,it is formulated as an integer-programming problem and a hybrid PSO-based heuristic algorithm is proposed,named improved PSOVNS,which integrates a variable neighborhood search within the Particle Swarm Optimization.[Findings]The algorithm is applied to solve a application example,and the convergence process and results are compared with the basic Particle Swarm algorithm.[Conclusions]The case study shows that the improved PSO-VNS algorithm can quickly jump out of local convergence,so its global searching ability is improved and the global convergence speed is faster.The improved PSO-VNS algorithm can provide a better solution for the distribution path of the collaterals.
作者
刘娜
高更君
李晓虹
LIU Na1 , GAO Gengjun1 , LI Xiaohong2(1. Logistics Research Center, Shanghai Maritime University, Shanghai 201306; 2. College of Computer and Information Science, Chongqing Normal University, Chongqing 401331, Chin)
出处
《重庆师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2018年第2期98-103,共6页
Journal of Chongqing Normal University:Natural Science
基金
国家自然科学基金(No.71601114)
上海市科委工程中心能力提升资助项目(No.14DZ2280200)
