Picking Route Optimization of Automated Warehouse Based on Improved Genetic Algorithms

被引：0
|
作者：
Wang, Peiguang [1 ]
Qi, Xingmin [1 ]
Zong, Xiaoping [1 ]
Zhu, Lingling [1 ]
机构：
[1] Hebei Univ, Coll Elect & Informat Engn, Hebei Baoding, Peoples R China
来源：
INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY II, PTS 1-4 | 2013年 / 411-414卷
关键词：
Automated warehouse; Stacker; Picking Route; Optimization; Improved Genetic Algorithms;
D O I：
10.4028/www.scientific.net/AMM.411-414.2694
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
In order to improve the efficiency of automated warehouse, the order-picking task of the fixed shelve was researched and analysed. The picking mathematical model of automated warehouse was established and attributed to the classical traveling salesman problem (TSP) model. At the same time, using an improved genetic algorithms(improved GAs) solved the optimization problem. Firstly, the initial population of the algorithm was optimized, and then a 'reverse evolution operator' was introduced in the improved genetic algorithms because of the lack of local optimization ability of genetic algorithm. Results of experiment verify that the method can acquire satisfying the demands of the route picking and optimization of speed.
引用
收藏
页码：2694 / 2697
页数：4
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