Presentation 2000/5/19
Solying Multi-Objective Flowshop Scheduling Problem by Improved Genetic Algorithm
Ishibashi Hiroyuki, Aguirre Hernan, Tanaka Kiyoshi, Sugimura Tatsuo,
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Abstract(in English) Because many problems in real world applications, such as decision making, include multiple objective functions in trade-off relationship, the problem often becomes a multi-objective optimization problem(MOP). In this work, we especially focus on solving the multi-objective flowshop scheduling problem(FSP), and try to obtain better pareto-optimum solutions(POS)by using an improved GA(GA-SRM). Two kinds of Cooperative-competitive genetic operators in GA-SRM(CM and SRM)are extended to the ones especially for FSP in which solutions (individuals)are represented as permutations. Simulation results verified that GA-SRM shows better performance even for MOP, and consequently better POS are obtained.
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Keyword(in English) genetic algorithms / multi-objective optimization problem / pareto-optimum solution / flowshop scheduling problem
Paper # AI2000-14
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Committee AI
Conference Date 2000/5/19(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Solying Multi-Objective Flowshop Scheduling Problem by Improved Genetic Algorithm
Sub Title (in English)
Keyword(1) genetic algorithms
Keyword(2) multi-objective optimization problem
Keyword(3) pareto-optimum solution
Keyword(4) flowshop scheduling problem
1st Author's Name Ishibashi Hiroyuki
1st Author's Affiliation Faculty of Engineering, Shinshu University()
2nd Author's Name Aguirre Hernan
2nd Author's Affiliation Faculty of Engineering, Shinshu University
3rd Author's Name Tanaka Kiyoshi
3rd Author's Affiliation Faculty of Engineering, Shinshu University
4th Author's Name Sugimura Tatsuo
4th Author's Affiliation Faculty of Engineering, Shinshu University
Date 2000/5/19
Paper # AI2000-14
Volume (vol) vol.100
Number (no) 89
Page pp.pp.-
#Pages 8
Date of Issue