DocumentCode
1738435
Title
A method for solving large-scale flowshop problems by reducing search space of genetic algorithms
Author
Yong, Zhao ; Sannomiya, Nobuo
Author_Institution
Dept. of Electron. & Inf. Sci., Kyoto Inst. of Technol., Japan
Volume
3
fYear
2000
fDate
2000
Firstpage
1776
Abstract
It is important to force search algorithms in promising regions of the solution space when solving large-scale problems. Genetic algorithms with search space reduction are proposed to solve flowshop problems. Additional precedence constraints generated by heuristic rules are introduced to reduce the search space of the genetic algorithm. An improved crossover operator which preserves the constraints is proposed and compared with other standard crossover operators. The computation results show that the algorithm has a significant improvement as compared with the standard genetic algorithms
Keywords
genetic algorithms; production control; search problems; crossover operator; genetic algorithms; heuristic rules; large-scale flowshop problem solving; precedence constraints; search space reduction; Biological cells; Convergence; Electronic mail; Genetic algorithms; Information science; Large-scale systems; Optimization methods; Processor scheduling; Robustness; Space technology;
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.2000.886366
Filename
886366
Link To Document