Research on Storage Optimization Problem Based on Improved Genetic Algorithm

被引：0
|
作者：
Ge, Mengyuan [1 ]
Li, Juntao [1 ]
机构：
[1] Beijing Wuzi Univ, Beijing, Peoples R China
来源：
2019 2ND INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING, INDUSTRIAL MATERIALS AND INDUSTRIAL ELECTRONICS (MEIMIE 2019) | 2019年
关键词：
Improved genetic algorithm; Warehouse storage optimization; Multi-objective function model;
D O I：
10.23977/meimie.2019.43030
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
The traditional genetic algorithm is easy to fall into the local optimal solution in the multi-objective function model of the distribution center warehouse, which produces many infeasible solutions. To this end, the paper proposes an improved genetic algorithm, using mutation operator selection and other items. By selecting the control parameters reasonably, it is possible to obtain relatively good individuals of each alphabet, and then select the optimal solution of multi-objective functions to reduce the defects of genetic algorithm. Finally, the paper validates the effectiveness of improved genetic algorithm in the storage location optimization of the distribution center warehouse.
引用
收藏
页码：181 / 186
页数：6
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