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Application of Adaptive Genetic Algorithm and Particle Swarm Optimisation in scheduling of jobs and AS/RS in FMS

Application of Adaptive Genetic Algorithm and Particle Swarm Optimisation in scheduling of jobs... Flexible Manufacturing Systems (FMS) are advanced production systems used in industries today. In this context, this paper deals with the problem of scheduling of jobs and Automated Storage and Retrieval Systems (AS/RS) assignments in a FMS environment because in some industries they have machines and this kind of AS/RS. Non-traditional optimisation techniques such as Adaptive Genetic Algorithm (AGA) and Particle Swarm Optimisation (PSO) are implemented to get optimal schedules and storage assignments. The objective function minimises the distance travelled by the Storage and Retrieval (S/R) machine. The results are presented and compared. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Manufacturing Research Inderscience Publishers

Application of Adaptive Genetic Algorithm and Particle Swarm Optimisation in scheduling of jobs and AS/RS in FMS

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References (19)

Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1750-0591
eISSN
1750-0605
DOI
10.1504/IJMR.2008.020901
Publisher site
See Article on Publisher Site

Abstract

Flexible Manufacturing Systems (FMS) are advanced production systems used in industries today. In this context, this paper deals with the problem of scheduling of jobs and Automated Storage and Retrieval Systems (AS/RS) assignments in a FMS environment because in some industries they have machines and this kind of AS/RS. Non-traditional optimisation techniques such as Adaptive Genetic Algorithm (AGA) and Particle Swarm Optimisation (PSO) are implemented to get optimal schedules and storage assignments. The objective function minimises the distance travelled by the Storage and Retrieval (S/R) machine. The results are presented and compared.

Journal

International Journal of Manufacturing ResearchInderscience Publishers

Published: Jan 1, 2008

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