吉林大学学报(理学版) ›› 2022, Vol. 60 ›› Issue (1): 127-0134.

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 基于多种群空间映射遗传算法的立体仓库储位优化

隋振, 张天星, 吴涛, 陈华锐   

  1. 吉林大学 通信工程学院, 长春 130012
  • 收稿日期:2021-01-18 出版日期:2022-01-26 发布日期:2022-01-26
  • 通讯作者: 隋振 E-mail:suizhen@jlu.edu.cn

Storage Optimization of Three-Dimensional Warehouse Based on Multi Population Space Mapping Genetic Algorithm

SUI Zhen, ZHANG Tianxing, WU Tao, CHEN Huarui   

  1. College of Communication Engineering, Jilin University, Changchun 130012, China
  • Received:2021-01-18 Online:2022-01-26 Published:2022-01-26

摘要: 针对在自动化立体仓库中储位分配混乱及仓储效率低的问题, 提出一个通过多种群空间映射遗传算法求解的组合优化模型. 该方法对基本遗传算法进行改进, 对货物自身需求量、 货架重心及货物相关性这3个方向组成的目标函数进行整体寻优. MATLAB仿真实验结果表明, 该方法得到了较现有算法更优的结果, 3个目标函数值均有改善, 并且任务容量会影响改进方法的优化能力.

关键词: 储位分配, 组合优化, 多目标函数建模, 遗传算法

Abstract: Aiming at the problems of chaotic storage allocation and low storage efficiency in automated three-dimensional warehouse, we proposed a combinatorial optimization model solved by a multi population space mapping genetic algorithm. The method improved the basic genetic algorithm and optimized the objective function composed of goods demand, shelf center of gravity and goods correlation. The MATLAB simulation results show that the method obtains better results than the existing algorithms, the values of the three objective functions are improved, and the task capacity can affect the optimization ability of the improved method.

Key words: storage allocation, combinatorial optimization, multi objective function modeling, genetic algorithm

中图分类号: 

  • TP391.9