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Effective heuristics for the blocking flowshop scheduling problem with makespan minimization

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  • Pan, Quan-Ke
  • Wang, Ling

Abstract

The blocking flowshop scheduling problem with makespan criterion has important applications in a variety of industrial systems. Heuristics that explore specific characteristics of the problem are essential for many practical systems to find good solutions with limited computational effort. This paper first presents two simple constructive heuristics, namely weighted profile fitting (wPF) and PW, based on the profile fitting (PF) approach of McCormick et al. [Sequencing in an assembly line with blocking to minimize cycle time. Operations Research 1989;37:925-36] and the characteristics of the problem. Then, three improved constructive heuristics, called PF-NEH, wPF-NEH, and PW-NEH, are proposed by combining the PF, wPF, and PW with the enumeration procedure of the Nawaz-Enscore-Ham (NEH) heuristic [A heuristic algorithm for the m-machine, n-job flow shop sequencing problem. OMEGA-International Journal of Management Science 1983;11:91-5] in an effective way. Thirdly, three composite heuristics i.e., PF-NEHLS, wPF-NEHLS, and PW-NEHLS, are developed by using the insertion-based local search method to improve the solutions generated by the constructive heuristics. Computational simulations and comparisons are carried out based on the well-known flowshop benchmarks of Taillard [Benchmarks for basic scheduling problems. European Journal of Operation Research 1993;64:278-85] that are considered as blocking flowshop instances. The results show that the presented constructive heuristics perform significantly better than the existing ones, and the proposed composite heuristics further improve the presented constructive heuristics by a considerable margin. In addition, 17 new best-known solutions for Taillard benchmarks with large scale are found by the presented heuristics.

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  • Pan, Quan-Ke & Wang, Ling, 2012. "Effective heuristics for the blocking flowshop scheduling problem with makespan minimization," Omega, Elsevier, vol. 40(2), pages 218-229, April.
    • Handle: RePEc:eee:jomega:v:40:y:2012:i:2:p:218-229
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    3. Shabtay, Dvir & Arviv, Kfir & Stern, Helman & Edan, Yael, 2014. "A combined robot selection and scheduling problem for flow-shops with no-wait restrictions," Omega, Elsevier, vol. 43(C), pages 96-107.
    4. Yunhe Wang & Xiangtao Li & Zhiqiang Ma, 2017. "A Hybrid Local Search Algorithm for the Sequence Dependent Setup Times Flowshop Scheduling Problem with Makespan Criterion," Sustainability, MDPI, vol. 9(12), pages 1-35, December.
    5. Pan, Quan-Ke & Ruiz, Rubén, 2014. "An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem," Omega, Elsevier, vol. 44(C), pages 41-50.
    6. Said Aqil & Karam Allali, 2021. "On a bi-criteria flow shop scheduling problem under constraints of blocking and sequence dependent setup time," Annals of Operations Research, Springer, vol. 296(1), pages 615-637, January.
    7. Marcelo Seido Nagano & Adriano Seiko Komesu & Hugo Hissashi Miyata, 2019. "An evolutionary clustering search for the total tardiness blocking flow shop problem," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1843-1857, April.
    8. Lin, Shih-Wei & Ying, Kuo-Ching, 2013. "Minimizing makespan in a blocking flowshop using a revised artificial immune system algorithm," Omega, Elsevier, vol. 41(2), pages 383-389.
    9. 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.
    10. Lin, Shih-Wei & Ying, Kuo-Ching, 2016. "Optimization of makespan for no-wait flowshop scheduling problems using efficient matheuristics," Omega, Elsevier, vol. 64(C), pages 115-125.
    11. Han, Yuyan & Wang, Yuting & Pan, Quan-ke & Wang, Ling & Tasgetiren, M. Fatih, 2024. "Accelerated evaluation of blocking flowshop scheduling with total flow time criteria using a generalized critical machine-based approach," European Journal of Operational Research, Elsevier, vol. 318(2), pages 424-441.
    12. Fernandez-Viagas, Victor & Talens, Carla & Prata, Bruno de Athayde, 2025. "A speed-up procedure and new heuristics for the classical job shop scheduling problem: A computational evaluation," European Journal of Operational Research, Elsevier, vol. 322(3), pages 783-794.
    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. Elisa Negri & Vibhor Pandhare & Laura Cattaneo & Jaskaran Singh & Marco Macchi & Jay Lee, 2021. "Field-synchronized Digital Twin framework for production scheduling with uncertainty," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 1207-1228, April.

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