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A modified particle swarm optimisation algorithm to solve the part feeding problem at assembly lines

Author

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  • Masood Fathi
  • Victoria Rodríguez
  • Dalila B.M.M. Fontes
  • Maria Jesus Alvarez

Abstract

The Assembly Line Part Feeding Problem (ALPFP) is a complex combinatorial optimisation problem concerned with the delivery of the required parts to the assembly workstations in the right quantities at the right time. Solving the ALPFP includes simultaneously solving two sub-problems, namely tour scheduling and tow-train loading. In this article, we first define the problem and formulate it as a multi-objective mixed-integer linear programming model. Then, we carry out a complexity analysis, proving the ALPFP to be NP-complete. A modified particle swarm optimisation (MPSO) algorithm incorporating mutation as part of the position updating scheme is subsequently proposed. The MPSO is capable of finding very good solutions with small time requirements. Computational results are reported, demonstrating the efficiency and effectiveness of the proposed MPSO.

Suggested Citation

  • Masood Fathi & Victoria Rodríguez & Dalila B.M.M. Fontes & Maria Jesus Alvarez, 2016. "A modified particle swarm optimisation algorithm to solve the part feeding problem at assembly lines," International Journal of Production Research, Taylor & Francis Journals, vol. 54(3), pages 878-893, February.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:3:p:878-893
    DOI: 10.1080/00207543.2015.1090032
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    References listed on IDEAS

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    1. Boysen, Nils & Emde, Simon & Hoeck, Michael & Kauderer, Markus, 2015. "Part logistics in the automotive industry: Decision problems, literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 242(1), pages 107-120.
    2. Boysen, Nils & Emde, Simon & Hoeck, Michael & Kauderer, Markus, 2015. "Part logistics in the automotive industry: Decision problems, literature review and research agenda," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 79443, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Simon Emde & Malte Fliedner & Nils Boysen, 2012. "Optimally loading tow trains for just-in-time supply of mixed-model assembly lines," IISE Transactions, Taylor & Francis Journals, vol. 44(2), pages 121-135.
    4. Emde, Simon & Fliedner, Malte & Boysen, Nils, 2012. "Optimally loading tow trains for just-in-time supply of mixed-model assembly lines," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 79434, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Frits K. Pil & Matthias Holweg, 2004. "Linking Product Variety to Order-Fulfillment Strategies," Interfaces, INFORMS, vol. 34(5), pages 394-403, October.
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    Cited by:

    1. Dalila B. M. M. Fontes & S. Mahdi Homayouni & Mauricio G. C. Resende, 2022. "Job-shop scheduling-joint consideration of production, transport, and storage/retrieval systems," Journal of Combinatorial Optimization, Springer, vol. 44(2), pages 1284-1322, September.
    2. Masood Fathi & Morteza Ghobakhloo, 2020. "Enabling Mass Customization and Manufacturing Sustainability in Industry 4.0 Context: A Novel Heuristic Algorithm for in-Plant Material Supply Optimization," Sustainability, MDPI, vol. 12(16), pages 1-15, August.
    3. Diefenbach, Heiko & Emde, Simon & Glock, Christoph H., 2020. "Loading tow trains ergonomically for just-in-time part supply," European Journal of Operational Research, Elsevier, vol. 284(1), pages 325-344.
    4. Simon Emde & Michael Schneider, 2018. "Just-In-Time Vehicle Routing for In-House Part Feeding to Assembly Lines," Transportation Science, INFORMS, vol. 52(3), pages 657-672, June.
    5. Beixin Xia & Mingyue Zhang & Yan Gao & Jing Yang & Yunfang Peng, 2023. "Design for Optimally Routing and Scheduling a Tow Train for Just-in-Time Material Supply of Mixed-Model Assembly Lines," Sustainability, MDPI, vol. 15(19), pages 1-16, October.
    6. Fontes, Dalila B.M.M. & Homayouni, S. Mahdi & Gonçalves, José F., 2023. "A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1140-1157.
    7. Diefenbach, Heiko & Emde, Simon & Glock, Christoph H., 2023. "Multi-depot electric vehicle scheduling in in-plant production logistics considering non-linear charging models," European Journal of Operational Research, Elsevier, vol. 306(2), pages 828-848.
    8. Emilio Moretti & Elena Tappia & Martina Mauri & Marco Melacini, 2022. "A performance model for mobile robot-based part feeding systems to supermarkets," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 580-613, September.

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