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Heuristics and metaheuristics for the distributed assembly permutation flowshop scheduling problem with sequence dependent setup times

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  • Hatami, Sara
  • Ruiz, Rubén
  • Andrés-Romano, Carlos

Abstract

We consider a Distributed Assembly Permutation Flowshop Scheduling Problem with sequence dependent setup times and the objective of makespan minimization. The problem consists of two stages, production and assembly. The first stage comprises f identical factories, where each factory is a flowshop that produces jobs which are later assembled into final products through an identical assembly program in a second assembly stage made by a single machine. Both stages have sequence dependent setup times. This is a realistic and complex problem and therefore, we propose two simple heuristics and two metaheuristics to solve it. A complete calibration and analysis through a Design Of Experiments (DOE) approach is carried out. In the process, important knowledge of the studied problem is obtained as well as some simplifications for the powerful Iterated Greedy methodology which results in a simpler approach with less parameters. Finally, the performance of the proposed methods is compared through extensive computational and statistical experiments.

Suggested Citation

  • Hatami, Sara & Ruiz, Rubén & Andrés-Romano, Carlos, 2015. "Heuristics and metaheuristics for the distributed assembly permutation flowshop scheduling problem with sequence dependent setup times," International Journal of Production Economics, Elsevier, vol. 169(C), pages 76-88.
    • Handle: RePEc:eee:proeco:v:169:y:2015:i:c:p:76-88
    DOI: 10.1016/j.ijpe.2015.07.027
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    References listed on IDEAS

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    Cited by:

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    2. Pourya Pourhejazy & Chen-Yang Cheng & Kuo-Ching Ying & Nguyen Hoai Nam, 2023. "Meta-Lamarckian-based iterated greedy for optimizing distributed two-stage assembly flowshops with mixed setups," Annals of Operations Research, Springer, vol. 322(1), pages 125-146, March.
    3. 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.
    4. Liou, Cheng-Dar & Hsieh, Yi-Chih, 2015. "A hybrid algorithm for the multi-stage flow shop group scheduling with sequence-dependent setup and transportation times," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 258-267.
    5. Bayliss, Christopher & Currie, Christine S.M. & Bennell, Julia A. & Martinez-Sykora, Antonio, 2019. "Dynamic pricing for vehicle ferries: Using packing and simulation to optimize revenues," European Journal of Operational Research, Elsevier, vol. 273(1), pages 288-304.
    6. Framinan, Jose M. & Perez-Gonzalez, Paz & Fernandez-Viagas, Victor, 2019. "Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures," European Journal of Operational Research, Elsevier, vol. 273(2), pages 401-417.
    7. Lorena Reyes-Rubiano & Laura Calvet & Angel A. Juan & Javier Faulin & Lluc Bové, 2020. "A biased-randomized variable neighborhood search for sustainable multi-depot vehicle routing problems," Journal of Heuristics, Springer, vol. 26(3), pages 401-422, June.
    8. 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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