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
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;
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.2000.886366
