DocumentCode :
1895579
Title :
Research on Hybrid-Genetic Algorithm for MAS Based Job-Shop Dynamic Scheduling
Author :
Li, Qingsong ; Du, Liming
Author_Institution :
Coll. of Traffic & Auto-mobile Eng., Xihua Univ., Chengdu, China
Volume :
1
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
404
Lastpage :
407
Abstract :
Aimed at the job-shop dynamic scheduling for agile manufacturing, genetic algorithms and heuristic rules are combined; a job-shop dynamic scheduling model based on multi-agent and the hybrid-genetic algorithm is proposed. The allocation of the tasks and coordination have been solved by multi-agent consultations based on contract net protocol, then the tasks have been rescheduled by hybrid-genetic algorithm in order to achieve global optimization. Finally, the feasibility and effectiveness of this method is confirmed by simulation.
Keywords :
agile manufacturing; dynamic scheduling; genetic algorithms; job shop scheduling; multi-agent systems; MAS; agile manufacturing; contract net protocol; heuristic rules; hybrid-genetic algorithm; job-shop dynamic scheduling model; multiagent system; Agile manufacturing; Contracts; Dynamic scheduling; Educational institutions; Genetic algorithms; Job shop scheduling; Multiagent systems; Protocols; Resource management; Scheduling algorithm; dynamic scheduling; hybrid-genetic algorithm; job-shop scheduling; multi-agent system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.105
Filename :
5287627
Link To Document :
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