Open Access
2013 Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms
Kuo-Yang Wu, Sendren Sheng-Dong Xu, Tzong-Chen Wu
Abstr. Appl. Anal. 2013(SI07): 1-17 (2013). DOI: 10.1155/2013/634812


We investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS) in the Flexible Manufacturing System (FMS) used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA), the Immune Genetic Algorithm (IGA), and the Particle Swarm Optimization (PSO) algorithm, are implemented to obtain the optimal assignments. The objective is to minimize the working distance, that is, the shortest retrieval time travelled by the Storage and Retrieval (S/R) machine. Simulation results and comparisons show the advantages and feasibility of the proposed methods.


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Kuo-Yang Wu. Sendren Sheng-Dong Xu. Tzong-Chen Wu. "Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms." Abstr. Appl. Anal. 2013 (SI07) 1 - 17, 2013.


Published: 2013
First available in Project Euclid: 26 February 2014

zbMATH: 07095191
MathSciNet: MR3073501
Digital Object Identifier: 10.1155/2013/634812

Rights: Copyright © 2013 Hindawi

Vol.2013 • No. SI07 • 2013
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