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A novel particle swarm optimization algorithm for permutation flow-shop scheduling to minimize makespan

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  • Lian, Zhigang
  • Gu, Xingsheng
  • Jiao, Bin

Abstract

It is well known that the flow-shop scheduling problem (FSSP) is a branch of production scheduling and is NP-hard. Now, many different approaches have been applied for permutation flow-shop scheduling to minimize makespan, but current algorithms even for moderate size problems cannot be solved to guarantee optimality. Some literatures searching PSO for continuous optimization problems are reported, but papers searching PSO for discrete scheduling problems are few. In this paper, according to the discrete characteristic of FSSP, a novel particle swarm optimization (NPSO) algorithm is presented and successfully applied to permutation flow-shop scheduling to minimize makespan. Computation experiments of seven representative instances (Taillard) based on practical data were made, and comparing the NPSO with standard GA, we obtain that the NPSO is clearly more efficacious than standard GA for FSSP to minimize makespan.

Suggested Citation

  • Lian, Zhigang & Gu, Xingsheng & Jiao, Bin, 2008. "A novel particle swarm optimization algorithm for permutation flow-shop scheduling to minimize makespan," Chaos, Solitons & Fractals, Elsevier, vol. 35(5), pages 851-861.
    • Handle: RePEc:eee:chsofr:v:35:y:2008:i:5:p:851-861
    DOI: 10.1016/j.chaos.2006.05.082
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    References listed on IDEAS

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    1. Allahverdi, Ali & Aldowaisan, Tariq, 2002. "New heuristics to minimize total completion time in m-machine flowshops," International Journal of Production Economics, Elsevier, vol. 77(1), pages 71-83, May.
    2. Liu, Bo & Wang, Ling & Jin, Yi-Hui & Tang, Fang & Huang, De-Xian, 2005. "Improved particle swarm optimization combined with chaos," Chaos, Solitons & Fractals, Elsevier, vol. 25(5), pages 1261-1271.
    3. Nearchou, A.C.Andreas C., 2004. "The effect of various operators on the genetic search for large scheduling problems," International Journal of Production Economics, Elsevier, vol. 88(2), pages 191-203, March.
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    Cited by:

    1. Alatas, Bilal & Akin, Erhan, 2009. "Chaotically encoded particle swarm optimization algorithm and its applications," Chaos, Solitons & Fractals, Elsevier, vol. 41(2), pages 939-950.
    2. Zahra Beheshti & Siti Shamsuddin & Siti Yuhaniz, 2013. "Binary Accelerated Particle Swarm Algorithm (BAPSA) for discrete optimization problems," Journal of Global Optimization, Springer, vol. 57(2), pages 549-573, October.
    3. 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.

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