DocumentCode
2669192
Title
Multi-objective optimization with improved genetic algorithm
Author
Ishibashi, Hiroyuki ; Aguirre, Hernán E. ; Tanaka, Kiyoshi ; Sugimura, Tatsuo
Author_Institution
Fac. of Eng., Shinshu Univ., Nagano, Japan
Volume
5
fYear
2000
fDate
2000
Firstpage
3852
Abstract
We extend an improved GA (GA-SRM) to the multi-objective flowshop scheduling problem (FSP) in order to obtain better pareto-optimum solutions (POS). Two kinds of cooperative-competitive genetic operators in GA-SRM, CM and SRM, are extended to ones suitable for FSP in which solutions (individuals) are represented as permutations. Simulation results verify that GA-SRM shows better performance for the multi-objective optimization problem (MOP), and consequently better POS are obtained than conventional approaches with canonical GA
Keywords
Pareto distribution; competitive algorithms; genetic algorithms; scheduling; cooperative-competitive genetic operators; genetic algorithm; multiobjective flowshop scheduling problem; multiobjective optimization; pareto-optimum solutions; permutations; Acceleration; Decision making; Evolutionary computation; Genetic algorithms; Genetic mutations; Marine vehicles; Random variables; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location
Nashville, TN
ISSN
1062-922X
Print_ISBN
0-7803-6583-6
Type
conf
DOI
10.1109/ICSMC.2000.886611
Filename
886611
Link To Document