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A Hybrid Approach for the Multi-Criteria-Based Optimization of Sequence-Dependent Setup-Based Flow Shop Scheduling

Author

Listed:
  • Fatih Yigit

    (Department of Industrial Engineering, Altinbas University, 34218 Istanbul, Turkey)

  • Marcio Pereira Basilio

    (Controladoria-Geral do Estado do Rio de Janeiro (CGE), Avenida Erasmo Braga, 118, Centro, Rio de Janeiro 20020-000, Brazil)

  • Valdecy Pereira

    (Department of Production Engineering, Fluminense Federal University (UFF), Niteroi 24210-240, Brazil)

Abstract

A key challenge in production management and operational research is the flow shop scheduling problem, characterized by its complexity in manufacturing processes. Traditional models often assume deterministic conditions, overlooking real-world uncertainties like fluctuating demand, variable processing times, and equipment failures, significantly impacting productivity and efficiency. The increasing demand for more adaptive and robust scheduling frameworks that can handle these uncertainties effectively drives the need for research in this area. Existing methods do not adequately capture modern manufacturing environments’ dynamic and unpredictable nature, resulting in inefficiencies and higher operational costs; they do not employ a fuzzy approach to benefit from human intuition. This study successfully demonstrates the application of Hexagonal Type-2 Fuzzy Sets (HT2FS) for the accurate modeling of the importance of jobs, thereby advancing fuzzy logic applications in scheduling problems. Additionally, it employs a novel Multi-Criteria Decision-Making (MCDM) approach employing Proportional Picture Fuzzy AHP (PPF-AHP) for group decision-making in a flow shop scheduling context. The research outlines the methodology involving three stages: group weight assessment through a PPF-AHP for the objectives, weight determination using HT2FS for the jobs, and optimization via Genetic Algorithm (GA), a method that gave us the optimal solution. This study contributes significantly to operational research and production scheduling by proposing a sophisticated, hybrid model that adeptly navigates the complexities of flow shop scheduling. The integration of HT2FS and MCDM techniques, particularly PPF-AHP, offers a novel approach that enhances decision-making accuracy and paves the way for future advancements in manufacturing optimization.

Suggested Citation

  • Fatih Yigit & Marcio Pereira Basilio & Valdecy Pereira, 2024. "A Hybrid Approach for the Multi-Criteria-Based Optimization of Sequence-Dependent Setup-Based Flow Shop Scheduling," Mathematics, MDPI, vol. 12(13), pages 1-24, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:13:p:2007-:d:1424664
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    References listed on IDEAS

    as
    1. Amorim, P. & Günther, H.-O. & Almada-Lobo, B., 2012. "Multi-objective integrated production and distribution planning of perishable products," International Journal of Production Economics, Elsevier, vol. 138(1), pages 89-101.
    2. Madjid Tavana & Mehdi Soltanifar & Francisco J. Santos-Arteaga, 2023. "Analytical hierarchy process: revolution and evolution," Annals of Operations Research, Springer, vol. 326(2), pages 879-907, July.
    3. Loukil, T. & Teghem, J. & Tuyttens, D., 2005. "Solving multi-objective production scheduling problems using metaheuristics," European Journal of Operational Research, Elsevier, vol. 161(1), pages 42-61, February.
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