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
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;
Conference_Titel :
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location :
Nashville, TN
Print_ISBN :
0-7803-6583-6
DOI :
10.1109/ICSMC.2000.886611
