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