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    Permutation flow shop scheduling: fuzzy particle swarm optimization approach

    Access Status
    Fulltext not available
    Authors
    Ling, S.
    Jiang, F.
    Chan, Kit Yan
    Nguyen, H.
    Date
    2011
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Ling, S.H. and Jiang, F. and Chan, K.Y. and Nguyen, H.T. 2011. Permutation flow shop scheduling: fuzzy particle swarm optimization approach, in IEEE International Conference on Fuzzy Systems (FUZZ 2011), Jun 27-30 2011. Taipei, Taiwan: IEEE.
    Source Title
    Proceedings of the IEEE international conference on fuzzy systems (FUZZ 2011)
    Source Conference
    IEEE International Conference on Fuzzy Systems (FUZZ 2011)
    DOI
    10.1109/FUZZY.2011.6007320
    ISSN
    1098-7584
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    URI
    http://hdl.handle.net/20.500.11937/7953
    Collection
    • Curtin Research Publications
    Abstract

    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.

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