摘要
针对冷链产品配送中动态需求处理不合理导致配送总成本高、车辆利用率低的问题,提出了动态分批优化和紧急订单即时重优化动态处理策略.考虑了静态客户订单取消、需求量增减和新增客户3种动态事件,并构建以配送总成本最小为目标的冷链车辆路径优化模型.基于先静态规划后动态调整的两阶段求解思想,采取更适用于在动态环境中寻优的粒子群算法求解,并引入relocate局部搜索算子来提高算法搜索精度.结果表明:与不考虑动态处理策略的优化方法相比,配送总成本减少26.68%,平均车辆有效利用率提高35.77%,验证了动态处理策略和算法的有效性.
Aiming at the problems of high total distribution cost and low vehicle utilization caused by unreasonable dynamic demand processing in cold chain product distribution,dynamic batch optimization and real-time re-optimization of urgent order dynamic processing strategies are proposed.Considering the three dynamic events of cancellation of static customer order,increase or decrease of demand and new customer demand,the model of cold chain vehicle routing problem(VRP)is constructed to minimize the total cost of distribution.Based on the two-stage solution idea of static planning before dynamic adjustment,particle swarm optimization(PSO),which is more suitable for optimization in dynamic environment,is adopted to solve the problem,and relocate local search operator is introduced to improve the search accuracy of the algorithm.The results show that the total cost of distribution is reduced by 26.68%and the average effective utilization ratio of vehicles is increased by 35.77%compared with the optimization method without considering the dynamic processing strategy,which verifies the effectiveness of the dynamic processing strategy and algorithm.
作者
刘艳秋
杨沙
LIU Yanqiu;YANG Sha(School of Science,Shenyang University of Technology,Shenyang 110870,China)
出处
《湖北民族大学学报(自然科学版)》
CAS
2022年第2期208-214,共7页
Journal of Hubei Minzu University:Natural Science Edition
基金
国家自然科学基金项目(70431003)
沈阳市科学技术计划项目(F14-231-1-24).
关键词
动态需求
冷链物流
动态处理策略
紧急订单
软时间窗
路径优化
粒子群算法
relocate算子
dynamic demand
cold chain logistics
dynamic processing strategy
urgent order
soft time window
path optimization
particle swarm optimization
relocate operator