Picking Route Optimization of Automated Warehouse Based on Improved Genetic Algorithms

Pei Guang Wang; Xing Min Qi; Xiao Ping Zong; Ling Ling Zhu

doi:10.4028/www.scientific.net/AMM.411-414.2694

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 411-414Picking Route Optimization of Automated Warehouse...

Picking Route Optimization of Automated Warehouse Based on Improved Genetic Algorithms

Abstract:

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 experiments verify that the method can acquire satisfying the demands of the route picking and optimization of speed.

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Periodical:

Applied Mechanics and Materials (Volumes 411-414)

Pages:

2694-2697

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.411-414.2694

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Online since:

September 2013

Authors:

Pei Guang Wang, Xing Min Qi, Xiao Ping Zong, Ling Ling Zhu

Keywords:

Automated Warehouse, Improved Genetic Algorithm (IGA), Optimization, Picking Route, Stacker

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