Title :
Flow Shop Scheduling Using an Improved PSO
Author_Institution :
Electron. Inf. Sch., Shanghai Dianji Univ., Shanghai, China
Abstract :
Particle swarm optimization (PSO) algorithm has shown some important advantages, but it has a tendency to get stuck in a local optimal solution. This paper presents an improved particle swarm optimization (IPSO) algorithm to improve the performance of traditional PSO, and it is applied to solve the flow shop scheduling problem and compared with GA and traditional PSO algorithm. Experimental results indicate that the IPSO algorithm for FSSP improves the search performance and shows the effectiveness of the algorithm to solve optimization problems.
Keywords :
flow shop scheduling; particle swarm optimisation; flow shop scheduling; improved particle swarm optimization algorithm; local optimal solution; Automation; Birds; Companies; Consumer electronics; Fluid flow measurement; Job shop scheduling; Manufacturing; Mechatronics; Particle swarm optimization; Scheduling algorithm; PSO; algorithm; flow shop; optimization;
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
Conference_Location :
Changsha City
Print_ISBN :
978-1-4244-5001-5
Electronic_ISBN :
978-1-4244-5739-7
DOI :
10.1109/ICMTMA.2010.455
