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
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