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A new vision of approximate methods for the permutation flowshop to minimise makespan: State-of-the-art and computational evaluation

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  • Fernandez-Viagas, Victor
  • Ruiz, Rubén
  • Framinan, Jose M.

Abstract

The permutation flowshop problem is a classic machine scheduling problem where n jobs must be processed on a set of m machines disposed in series and where each job must visit all machines in the same order. Many production scheduling problems resemble flowshops and hence it has generated much interest and had a big impact in the field, resulting in literally hundreds of heuristic and metaheuristic methods over the last 60 years. However, most methods proposed for makespan minimisation are not properly compared with existing procedures so currently it is not possible to know which are the most efficient methods for the problem regarding the quality of the solutions obtained and the computational effort required. In this paper, we identify and exhaustively compare the best existing heuristics and metaheuristics so the state-of-the-art regarding approximate procedures for this relevant problem is established.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ejores:v:257:y:2017:i:3:p:707-721
    DOI: 10.1016/j.ejor.2016.09.055
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    Cited by:

    1. Yong Wang & Yuting Wang & Yuyan Han, 2023. "A Variant Iterated Greedy Algorithm Integrating Multiple Decoding Rules for Hybrid Blocking Flow Shop Scheduling Problem," Mathematics, MDPI, vol. 11(11), pages 1-25, May.
    2. Benavides, Alexander J. & Vera, Antony, 2022. "The reversibility property in a job-insertion tiebreaker for the permutational flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 297(2), pages 407-421.
    3. Franzin, Alberto & Stützle, Thomas, 2023. "A landscape-based analysis of fixed temperature and simulated annealing," European Journal of Operational Research, Elsevier, vol. 304(2), pages 395-410.
    4. Victor Fernandez-Viagas & Luis Sanchez-Mediano & Alvaro Angulo-Cortes & David Gomez-Medina & Jose Manuel Molina-Pariente, 2022. "The Permutation Flow Shop Scheduling Problem with Human Resources: MILP Models, Decoding Procedures, NEH-Based Heuristics, and an Iterated Greedy Algorithm," Mathematics, MDPI, vol. 10(19), pages 1-32, September.
    5. Jiang, Junwei & An, Youjun & Dong, Yuanfa & Hu, Jiawen & Li, Yinghe & Zhao, Ziye, 2023. "Integrated optimization of non-permutation flow shop scheduling and maintenance planning with variable processing speed," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    6. Maria Raquel C. Costa & Jorge M. S. Valente & Jeffrey E. Schaller, 2020. "Efficient procedures for the weighted squared tardiness permutation flowshop scheduling problem," Flexible Services and Manufacturing Journal, Springer, vol. 32(3), pages 487-522, September.
    7. Pessoa, Luciana S. & Andrade, Carlos E., 2018. "Heuristics for a flowshop scheduling problem with stepwise job objective function," European Journal of Operational Research, Elsevier, vol. 266(3), pages 950-962.
    8. Karimi-Mamaghan, Maryam & Mohammadi, Mehrdad & Pasdeloup, Bastien & Meyer, Patrick, 2023. "Learning to select operators in meta-heuristics: An integration of Q-learning into the iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1296-1330.
    9. Brammer, Janis & Lutz, Bernhard & Neumann, Dirk, 2022. "Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning," European Journal of Operational Research, Elsevier, vol. 299(1), pages 75-86.
    10. Fernandez-Viagas, Victor & Molina-Pariente, Jose M. & Framinan, Jose M., 2020. "Generalised accelerations for insertion-based heuristics in permutation flowshop scheduling," European Journal of Operational Research, Elsevier, vol. 282(3), pages 858-872.
    11. S. S. Panwalkar & Christos Koulamas, 2019. "The evolution of schematic representations of flow shop scheduling problems," Journal of Scheduling, Springer, vol. 22(4), pages 379-391, August.
    12. Liu, Weibo & Jin, Yan & Price, Mark, 2017. "A new improved NEH heuristic for permutation flowshop scheduling problems," International Journal of Production Economics, Elsevier, vol. 193(C), pages 21-30.
    13. Joaquín Bautista-Valhondo & Rocío Alfaro-Pozo, 2020. "Mixed integer linear programming models for Flow Shop Scheduling with a demand plan of job types," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 5-23, March.
    14. Lobo, Fernando G. & Bazargani, Mosab & Burke, Edmund K., 2020. "A cutoff time strategy based on the coupon collector’s problem," European Journal of Operational Research, Elsevier, vol. 286(1), pages 101-114.
    15. Perez-Gonzalez, Paz & Framinan, Jose M., 2024. "A review and classification on distributed permutation flowshop scheduling problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 1-21.
    16. Gmys, Jan & Mezmaz, Mohand & Melab, Nouredine & Tuyttens, Daniel, 2020. "A computationally efficient Branch-and-Bound algorithm for the permutation flow-shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 284(3), pages 814-833.
    17. Pagnozzi, Federico & Stützle, Thomas, 2019. "Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems," European Journal of Operational Research, Elsevier, vol. 276(2), pages 409-421.
    18. Fernando Luis Rossi & Marcelo Seido Nagano, 2022. "Beam search-based heuristics for the mixed no-idle flowshop with total flowtime criterion," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1311-1346, December.
    19. Ruiz, Rubén & Pan, Quan-Ke & Naderi, Bahman, 2019. "Iterated Greedy methods for the distributed permutation flowshop scheduling problem," Omega, Elsevier, vol. 83(C), pages 213-222.

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