DocumentCode :
3540569
Title :
Hybrid Particle Swarm Optimization with parameter selection approaches to solve Flow Shop Scheduling Problem
Author :
Zhang, Xue-Feng ; An, Xuanye ; Koshimura, Miyuki ; Fujita, Hiroshi ; Hasegawa, Ryuzo
Author_Institution :
Grad. Sch. of Inf., Sci. & Electr. Eng., Kyushu Univ., Fukuoka, Japan
fYear :
2011
fDate :
1-2 Sept. 2011
Firstpage :
13
Lastpage :
19
Abstract :
A Hybrid Particle Swarm Optimization (HPSO) with parameter selection approaches is proposed to solve Flow Shop Scheduling Problem (FSSP) with the objective of minimizing makespan. The HPSO integrates the basic structure of a Particle Swarm Optimization (PSO) together with features borrowed from the fields of Tabu Search (TS), Simulated Annealing (SA). The algorithm works from a population of candidate schedules and generates new populations of neighbor and cooling schedules by applying suitable small perturbation schemes. Furthermore, PSO is very sensitive to efficient parameter setting such that modifying a single parameter may cause a considerable change in the result. Another two classes of new adaptive selection of value for inertia weight and acceleration coefficients are introduced into it. Extensive experiments on different scale benchmarks validate the effectiveness of our approaches, compared with other well-established methods. The experimental results show that new upper bounds of some unsolved problems and better solutions in a relatively reasonable time. In addition, proposed algorithms converge to stopping criteria significantly faster.
Keywords :
flow shop scheduling; particle swarm optimisation; search problems; simulated annealing; HPSO; flow shop scheduling; hybrid particle swarm optimization; parameter selection; simulated annealing; tabu search; Acceleration; Educational institutions; Equations; Job shop scheduling; Optimization; Particle swarm optimization; Schedules; flow shop scheduling problem; inertia weight; mutation; particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cybernetic Intelligent Systems (CIS), 2011 IEEE 10th International Conference on
Conference_Location :
London
Print_ISBN :
978-1-4673-0687-4
Type :
conf
DOI :
10.1109/CIS.2011.6169128
Filename :
6169128
Link To Document :
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