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
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;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1380676
