基于PSO-GA算法的后方仓库货位分配优化  

Optimization of Location Allocation in Rear Warehouse Based on PSO-GA Algorithm

作　　者：邱雄飞 张桦 赵润泽 QIU Xiongfei;ZHANG Hua;ZHAO Runze(Shijiazhuang Campus of Army Engineering University,Shijiazhuang 050003,China;The 3rd Military Representative Office Stationed in Shijiazhuang Region of the Army Equipment Department,Shijiazhuang 050051,China)

机构地区：[1]陆军工程大学石家庄校区,河北石家庄050003 [2]陆军装备部驻石家庄地区第三军事代表室,河北石家庄050051

出　　处：《信息工程大学学报》2024年第4期423-427,共5页Journal of Information Engineering University

摘　　要：针对当前部队后方仓库的货位分配效率不高的问题,将传统的粒子群优化(PSO)算法和遗传算法(GA)相结合,构建一种混合求解模型。结合实例通过仿真分析表明,该混合算法与传统的PSO和GA相比,具有一定的优越性,能够有效提高仓库作业效率和货架稳定性,对后方仓库的货位分配研究具有一定的理论价值和实践意义。To address the problem of inefficient allocation of cargo space in the rear warehouse of the current army,a hybrid solution model of particle swarm optimization(PSO)algorithm and genetic algorithm(GA)is established.Simulation analysis shows that the hybrid algorithm has certain advantages compared with the traditional PSO and GA algorithms,which can effectively improve the efficiency of warehouse operation and shelf stability.It has certain theoretical value and practical significance for the research of location allocation in the rear warehouse.

关 键 词：后方仓库 货位分配 粒子群算法 遗传算法 多目标优化 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]