Hybrid flow-shop scheduling method based on multi-agent particle swarm optimization

Author

Yue-wen, Fu ; Feng-xing, Zou ; Xiao-hong, Xu ; Qing-zhu, Cui ; Jia-hua, Wei

Author_Institution

Coll. of Mechatron. & Autom., Nat. Univ. of Defense Technol., Changsha, China

fYear

2011

fDate

6-8 June 2011

Firstpage

755

Lastpage

759

Abstract

In this paper, a multi-agent particle swarm optimization (MPSO) based on multi-agent system (MAS) and PSO was proposed for hybrid flow-shop scheduling problem (HFSP), and a random cycle topological structure is presented related to MPSO. In MAS, every particle represents an agent, and it can cooperate and compete with the agent around and do self-learning. Using these agent interactions and the evolution mechanism of PSO, MPSO can find the global optimum more accurately. The result of simulation proved that this algorithm has a higher searching efficiency and better optimal searching performance.

Keywords

flow shop scheduling; multi-agent systems; particle swarm optimisation; MPSO; hybrid flow-shop scheduling method; multiagent particle swarm optimization; random cycle topological structure; searching efficiency; Algorithm design and analysis; Encoding; Equations; Job shop scheduling; Mathematical model; Particle swarm optimization; Hybrid Flow-shop; Multi-agent System; Particle Swarm Optimization; Topological Structure;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Automation (ICIA), 2011 IEEE International Conference on

Conference_Location

Shenzhen

Print_ISBN

978-1-4577-0268-6

Electronic_ISBN

978-1-4577-0269-3

Type

conf

DOI

10.1109/ICINFA.2011.5949094

Filename

5949094