Title :
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
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;
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
DOI :
10.1109/ICINFA.2011.5949094
