DocumentCode :
2503039
Title :
Research on particle swarm optimization in location assignment optimization
Author :
Chen, Yueting ; He, Fang
Author_Institution :
Sch. of Control Sci. & Eng., Univ. of Jinan, Jinan
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
111
Lastpage :
116
Abstract :
With the development of logistics technology, automated storage and retrieval systems (AS/RS) is more widely used in logistics industry. It has been a hot research of improving the efficiency of automatic warehouse by the reasonable control strategy of location assignment. In this paper, the location assignment strategies of an automated warehouse were discussed, and the mathematical model of the location assignment optimization was built. Improved particle swarm optimization (PSO) based on Pareto optimal solution is proposed to deal with the problem of the location assignment. In the algorithm, the concept of permutation was introduced to calculate the velocity and position of the particle. In the process of optimization, Niche technique has been used to improve the diversity of non-dominated solutions. Archive was used to reserve all the non-dominated solutions to the result. The simulation experiment was given, and the result was analyzed. The problem of location assignment optimization could be effectively resolved by the improved particle swarm optimization proposed.
Keywords :
logistics; particle swarm optimisation; warehouse automation; automated storage; automated warehouse; location assignment optimization; particle swarm optimization; retrieval systems; Analytical models; Automatic control; Control systems; Electrical equipment industry; Intelligent control; Iterative algorithms; Logistics; Mathematical model; Particle swarm optimization; Storage automation; Pareto; automated warehouse; location assignment; particle swarm optimization (PSO); permutation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4594428
Filename :
4594428
Link To Document :
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