DocumentCode
2319729
Title
Multi-agent based genetic algorithm for JSSP
Author
Chen, Yan ; Li, Zeng-Zhi ; Wang, Zhi-Wen
Author_Institution
Inst. of Comput. Archit. & Network, Xi´´an Jiaotong Univ., China
Volume
1
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
267
Abstract
A novel multi-agent based on genetic algorithm (GA) is proposed to solve job-shop scheduling problem (JSSP). This algorithm not only can accelerate the creation of initial population and the selection of evaluation population, but also can control the processing of selection, crossover and mutation in an intelligent way. Job-shop benchmarks are used to evaluate the efficiency and performance of the proposed algorithm. The experimental result shows it has better optimal performance.
Keywords
benchmark testing; genetic algorithms; job shop scheduling; multi-agent systems; evaluation population; job-shop benchmarks; job-shop scheduling problem; multiagent based genetic algorithm; Acceleration; Computer architecture; Electronic mail; Genetic algorithms; Genetic mutations; NP-complete problem; Processor scheduling; Profitability;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1380676
Filename
1380676
Link To Document