DocumentCode :
3462034
Title :
New Particle Swarm Optimization Algorithm for Makespan Minimization in Permutation Flowshop Sequencing
Author :
Chen, Ting-Yu ; Chen, Chuen-Lung
Author_Institution :
Dept. of Manage. Inf. Syst., Nat. Chengchi Univ., Taipei, Taiwan
fYear :
2009
fDate :
7-9 Dec. 2009
Firstpage :
868
Lastpage :
871
Abstract :
Particle Swarm Optimization (PSO) is a new type of heuristic inspired by the flocking behavior of birds. This paper presents a Particle Swarm Optimization (PSO) to solve the permutation flowshop scheduling problem (PFSP) objectives, to minimize the makespan. To this end, we have proposed the use of discrete PSO algorithm for the position of the smallest value (SPV) to use a random key representation of Bean [Baena Bean, Genetic algorithms and random keys sequencing and optimization, Orsa calculated Journal 6 (2) ( 1994) 154-160]. In the proposed algorithm, the particle and the velocity re-defined and effective way to develop a series of new particles. In addition, we analyzed the characteristics of the elite jobs in the proposed algorithm. The results showed that the idea really follows the approach of PSO.
Keywords :
flow shop scheduling; particle swarm optimisation; particle swarm optimization; permutation flowshop scheduling problem; random key representation; smallest value position; Acceleration; Algorithm design and analysis; Birds; Control systems; Equations; Genetic algorithms; Genetic programming; Management information systems; Minimization methods; Particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4244-5543-0
Type :
conf
DOI :
10.1109/ICICIC.2009.278
Filename :
5412652
Link To Document :
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