Title :
Research on hybrid-genetic algorithm for MAS based job-shop dynamic scheduling
Author :
Qingsong, Li ; Dan, Qu ; Liming, Du
Author_Institution :
Coll. of Auto-mobile & trans. Eng, Xihua Univ., Chengdu
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 effectiveness of this method is confirmed by simulation.
Keywords :
agile manufacturing; dynamic scheduling; genetic algorithms; job shop scheduling; multi-agent systems; protocols; MAS; agile manufacturing; contract net protocol; global optimization; heuristic rule; hybrid-genetic algorithm; job-shop dynamic scheduling; multiagent system consultation; task allocation; Hybrid-genetic Algorithm; Job-shop Dynamic Scheduling; Multi-Agent System (MAS);
Conference_Titel :
Service Operations and Logistics, and Informatics, 2008. IEEE/SOLI 2008. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2012-4
Electronic_ISBN :
978-1-4244-2013-1
DOI :
10.1109/SOLI.2008.4682810
