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A Survey on Parallel Genetic Algorithms for Shop Scheduling Problems

Jia Luo 1 Didier El Baz 1
1 LAAS-CDA - Équipe Calcul Distribué et Asynchronisme
LAAS - Laboratoire d'analyse et d'architecture des systèmes
Abstract : There have been extensive works dealing with genetic algorithms (GAs) for seeking optimal solutions of shop scheduling problems. Due to the NP hardness, the time cost is always heavy. With the development of high performance computing (HPC) in last decades, the interest has been focused on parallel GAs for shop scheduling problems. In this paper, we present the state of the art with respect to the recent works on solving shop scheduling problems using parallel GAs. It showcases the most representative publications in this field by the categorization of parallel GAs and analyzes their designs based on the frameworks.
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Contributor : Didier El Baz <>
Submitted on : Saturday, April 6, 2019 - 9:51:51 AM
Last modification on : Thursday, June 10, 2021 - 3:01:22 AM


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Jia Luo, Didier El Baz. A Survey on Parallel Genetic Algorithms for Shop Scheduling Problems. IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW 2018), May 2018, Vancouver, Canada. pp.629-636, ⟨10.1109/IPDPSW.2018.00103⟩. ⟨hal-02091699⟩



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