摘要
为了有效解决多仓库多配送点物流配送时间长和路径远等问题,提出一种多仓库多配送点物流配送路径优化算法。为了满足多仓库多配送点物流配送需求,将最少调用车辆数量和最短配送总距离为目标,确定目标函数及其约束条件,建立多仓库多配送点物流配送路径优化模型。改进布谷鸟算法和粒子群算法,将改进后的算法结合,利用混合自适应布谷鸟算法求解优化模型,同时对混合自适应布谷鸟算法离散化处理,获取最优物流配送路径。仿真实验结果表明,所提算法可以在较短的时间内完成物流配送,且物流运输路径较短,覆盖率更广,能够获取更加满意的物流配送方案。
In order to effectively solve the problems of long logistics distribution time and long path in multiwarehouse and multi-distribution points,this article proposed an optimization algorithm for logistics distribution path in multi-warehouse and multi-distribution points.In order to meet the needs of logistics distribution,we used the minimum number of vehicles to be called and the shortest total delivery distance to determine the objective function and its constraints.Moreover,we constructed a model of optimizing logistics distribution path in multi-warehouse and multi-distribution points.Furthermore,we improved the cuckoo algorithm and particle swarm algorithm,and then combined them to create a hybrid adaptive cuckoo algorithm for solving the optimization model.Meanwhile,we discretized the hybrid adaptive cuckoo algorithm to obtain the optimal logistics distribution path.The simulation results show that the proposed algorithm can complete logistics distribution in a shorter time in a shorter time,with shorter logistics transportation path and wider coverage,and can obtain more satisfactory logistics distribution sulutions.
作者
任晓玲
赵涓涓
任佳丽
REN Xiao-ling;ZHAO Juan-juan;REN Jia-li(Taiyuan University of Technology,Jinzhong Shanxi 030600,China)
出处
《计算机仿真》
2024年第5期168-171,241,共5页
Computer Simulation
关键词
多仓库
多配送点
物流配送
路径优化
混合自适应布谷鸟算法
Multi warehouse
Multiple distribution points
Logistics distribution
Path optimization
Hybrid adaptive cuckoo algorithm
