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A discrete particle swarm optimization for lot-streaming flowshop scheduling problem

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  • Tseng, Chao-Tang
  • Liao, Ching-Jong

Abstract

We consider an n-job, m-machine lot-streaming problem in a flowshop with equal-size sublots where the objective is to minimize the total weighted earliness and tardiness. To solve this problem, we first propose a so-called net benefit of movement (NBM) algorithm, which is much more efficient than the existing linear programming model for obtaining the optimal starting and completion times of sublots for a given job sequence. A new discrete particle swarm optimization (DPSO) algorithm incorporating the NBM algorithm is then developed to search for the best sequence. The new DPSO improves the existing DPSO by introducing an inheritance scheme, inspired by a genetic algorithm, into particles construction. To verify the proposed DPSO algorithm, comparisons with the existing DPSO algorithm and a hybrid genetic algorithm (HGA) are made. Computational results show that the proposed DPSO algorithm with a two-point inheritance scheme is very competitive for the lot-streaming flowshop scheduling problem.

Suggested Citation

  • Tseng, Chao-Tang & Liao, Ching-Jong, 2008. "A discrete particle swarm optimization for lot-streaming flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 191(2), pages 360-373, December.
  • Handle: RePEc:eee:ejores:v:191:y:2008:i:2:p:360-373
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    References listed on IDEAS

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    1. Kalir, Adar A. & Sarin, Subhash C., 2001. "A near-optimal heuristic for the sequencing problem in multiple-batch flow-shops with small equal sublots," Omega, Elsevier, vol. 29(6), pages 577-584, December.
    2. Tasgetiren, M. Fatih & Liang, Yun-Chia & Sevkli, Mehmet & Gencyilmaz, Gunes, 2007. "A particle swarm optimization algorithm for makespan and total flowtime minimization in the permutation flowshop sequencing problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1930-1947, March.
    3. Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
    4. Stanley Reiter, 1965. "A System for Managing Job-Shop Production," The Journal of Business, University of Chicago Press, vol. 39, pages 371-371.
    5. Dan Trietsch & Kenneth R. Baker, 1993. "Basic Techniques for Lot Streaming," Operations Research, INFORMS, vol. 41(6), pages 1065-1076, December.
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    Cited by:

    1. Pan, Quan-Ke & Ruiz, Rubén, 2012. "An estimation of distribution algorithm for lot-streaming flow shop problems with setup times," Omega, Elsevier, vol. 40(2), pages 166-180, April.
    2. Zoltán Varga & Pál Simon, 2014. "Examination Of Scheduling Methods For Production Systems," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 8(1), pages 111-120, December.
    3. Buscher, Udo & Shen, Liji, 2009. "An integrated tabu search algorithm for the lot streaming problem in job shops," European Journal of Operational Research, Elsevier, vol. 199(2), pages 385-399, December.
    4. Hong-Yan Sang & Quan-Ke Pan & Pei-Yong Duan & Jun-Qing Li, 2018. "An effective discrete invasive weed optimization algorithm for lot-streaming flowshop scheduling problems," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1337-1349, August.
    5. Goh, C.K. & Tan, K.C. & Liu, D.S. & Chiam, S.C., 2010. "A competitive and cooperative co-evolutionary approach to multi-objective particle swarm optimization algorithm design," European Journal of Operational Research, Elsevier, vol. 202(1), pages 42-54, April.
    6. Cho, Huidae & Kim, Dongkyun & Olivera, Francisco & Guikema, Seth D., 2011. "Enhanced speciation in particle swarm optimization for multi-modal problems," European Journal of Operational Research, Elsevier, vol. 213(1), pages 15-23, August.
    7. Shih-Che Lo, 2022. "A Particle Swarm Optimization Approach to Solve the Vehicle Routing Problem with Cross-Docking and Carbon Emissions Reduction in Logistics Management," Logistics, MDPI, vol. 6(3), pages 1-15, September.

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