Permutation flow shop scheduling: fuzzy particle swarm optimization approach

A fuzzy particle swarm optimization (PSO) for the minimization of makespan in permutation flow shop scheduling problem is presented in this paper. In the proposed fuzzy PSO, the inertia weight of PSO and the control parameter of the cross-mutated operation are determined by a set of fuzzy rules. To...

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Main Authors: Ling, S., Jiang, F., Chan, Kit Yan, Nguyen, H.
Other Authors: Chin-Teng Lin
Format: Conference Paper
Published: IEEE 2011
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/7953
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author Ling, S.
Jiang, F.
Chan, Kit Yan
Nguyen, H.
author2 Chin-Teng Lin
author_facet Chin-Teng Lin
Ling, S.
Jiang, F.
Chan, Kit Yan
Nguyen, H.
author_sort Ling, S.
building Curtin Institutional Repository
collection Online Access
description A fuzzy particle swarm optimization (PSO) for the minimization of makespan in permutation flow shop scheduling problem is presented in this paper. In the proposed fuzzy PSO, the inertia weight of PSO and the control parameter of the cross-mutated operation are determined by a set of fuzzy rules. To escape the local optimum, cross-mutated operation is introduced. In order to make PSO suitable for solving permutation flow shop scheduling problem, a roulette wheel mechanism is proposed to convert the continuous position values of particles to job permutations. Meanwhile, a swap-based local search for scheduling problem is designed for the local exploration on a discrete job permutation space. Flow shop benchmark functions are employed to evaluate the performance of the fuzzy PSO for flow shop scheduling problems and the results indicate that the algorithm performs better compared with existing hybrid PSO algorithms.
first_indexed 2025-11-14T06:18:37Z
format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T06:18:37Z
publishDate 2011
publisher IEEE
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spelling curtin-20.500.11937-79532023-01-18T08:46:47Z Permutation flow shop scheduling: fuzzy particle swarm optimization approach Ling, S. Jiang, F. Chan, Kit Yan Nguyen, H. Chin-Teng Lin Yau-Huang Kuo Flow shop scheduling Fuzzy logic Particle swarm optimization A fuzzy particle swarm optimization (PSO) for the minimization of makespan in permutation flow shop scheduling problem is presented in this paper. In the proposed fuzzy PSO, the inertia weight of PSO and the control parameter of the cross-mutated operation are determined by a set of fuzzy rules. To escape the local optimum, cross-mutated operation is introduced. In order to make PSO suitable for solving permutation flow shop scheduling problem, a roulette wheel mechanism is proposed to convert the continuous position values of particles to job permutations. Meanwhile, a swap-based local search for scheduling problem is designed for the local exploration on a discrete job permutation space. Flow shop benchmark functions are employed to evaluate the performance of the fuzzy PSO for flow shop scheduling problems and the results indicate that the algorithm performs better compared with existing hybrid PSO algorithms. 2011 Conference Paper http://hdl.handle.net/20.500.11937/7953 10.1109/FUZZY.2011.6007320 IEEE restricted
spellingShingle Flow shop scheduling
Fuzzy logic
Particle swarm optimization
Ling, S.
Jiang, F.
Chan, Kit Yan
Nguyen, H.
Permutation flow shop scheduling: fuzzy particle swarm optimization approach
title Permutation flow shop scheduling: fuzzy particle swarm optimization approach
title_full Permutation flow shop scheduling: fuzzy particle swarm optimization approach
title_fullStr Permutation flow shop scheduling: fuzzy particle swarm optimization approach
title_full_unstemmed Permutation flow shop scheduling: fuzzy particle swarm optimization approach
title_short Permutation flow shop scheduling: fuzzy particle swarm optimization approach
title_sort permutation flow shop scheduling: fuzzy particle swarm optimization approach
topic Flow shop scheduling
Fuzzy logic
Particle swarm optimization
url http://hdl.handle.net/20.500.11937/7953