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A genetic algorithm for flow shop scheduling problems

Author

Listed:
  • O Etiler

    (ŞIŞECAM)

  • B Toklu

    (Gazi University)

  • M Atak

    (Loughborough University)

  • J Wilson

    (Loughborough University)

Abstract

Many scheduling problems are NP-hard problems. For such NP-hard combinatorial optimization problems, heuristics play a major role in searching for near-optimal solutions. In this paper we develop a genetic algorithm-based heuristic for the flow shop scheduling problem with makespan as the criterion. The performance of the algorithm is compared with the established NEH algorithm. Computational experience indicates that genetic algorithms can be good techniques for flowshop scheduling problems.

Suggested Citation

  • O Etiler & B Toklu & M Atak & J Wilson, 2004. "A genetic algorithm for flow shop scheduling problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 830-835, August.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:8:d:10.1057_palgrave.jors.2601766
    DOI: 10.1057/palgrave.jors.2601766
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    References listed on IDEAS

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    1. David G. Dannenbring, 1977. "An Evaluation of Flow Shop Sequencing Heuristics," Management Science, INFORMS, vol. 23(11), pages 1174-1182, July.
    2. Herbert G. Campbell & Richard A. Dudek & Milton L. Smith, 1970. "A Heuristic Algorithm for the n Job, m Machine Sequencing Problem," Management Science, INFORMS, vol. 16(10), pages 630-637, June.
    3. Chen, Chuen-Lung & Vempati, Venkateswara S. & Aljaber, Nasser, 1995. "An application of genetic algorithms for flow shop problems," European Journal of Operational Research, Elsevier, vol. 80(2), pages 389-396, January.
    4. Ho, Johnny C. & Chang, Yih-Long, 1991. "A new heuristic for the n-job, M-machine flow-shop problem," European Journal of Operational Research, Elsevier, vol. 52(2), pages 194-202, May.
    5. Koulamas, Christos, 1998. "A new constructive heuristic for the flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 105(1), pages 66-71, February.
    6. Framinan, J. M. & Leisten, R., 2003. "An efficient constructive heuristic for flowtime minimisation in permutation flow shops," Omega, Elsevier, vol. 31(4), pages 311-317, August.
    7. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. G I Zobolas & C D Tarantilis & G Ioannou, 2009. "A hybrid evolutionary algorithm for the job shop scheduling problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 221-235, February.
    2. Z P Fan & Y Chen & J Ma & S Zeng, 2011. "A hybrid genetic algorithmic approach to the maximally diverse grouping problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 92-99, January.
    3. Vallada, Eva & Ruiz, Rubén, 2010. "Genetic algorithms with path relinking for the minimum tardiness permutation flowshop problem," Omega, Elsevier, vol. 38(1-2), pages 57-67, February.
    4. Z P Fan & Y Chen & J Ma & S Zeng, 2011. "Erratum: A hybrid genetic algorithmic approach to the maximally diverse grouping problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1423-1430, July.
    5. Fernandez-Viagas, Victor & Ruiz, Rubén & Framinan, Jose M., 2017. "A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation," European Journal of Operational Research, Elsevier, vol. 257(3), pages 707-721.
    6. J Jackman & Z Guerra de Castillo & S Olafsson, 2011. "Stochastic flow shop scheduling model for the Panama Canal," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 69-80, January.
    7. J N D Gupta & J E Schaller, 2006. "Minimizing flow time in a flow-line manufacturing cell with family setup times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(2), pages 163-176, February.
    8. Chia-Shin Chung & James Flynn & Walter Rom & Piotr Staliński, 2012. "A Genetic Algorithm to Minimize the Total Tardiness for M-Machine Permutation Flowshop Problems," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 8(2), pages 26-43.

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