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An iterated greedy algorithm for the flowshop scheduling problem with blocking

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  • Ribas, Imma
  • Companys, Ramon
  • Tort-Martorell, Xavier

Abstract

This paper proposes an iterated greedy algorithm for solving the blocking flowshop scheduling problem for makespan minimization. Moreover, it presents an improved NEH-based heuristic, which is used as the initial solution procedure for the iterated greedy algorithm. The effectiveness of both procedures was tested on some of Taillard's benchmark instances that are considered to be blocking flowshop instances. The experimental evaluation showed the efficiency of the proposed algorithm, in spite of its simple structure, in comparison with a state-of-the-art algorithm. In addition, new best solutions for Taillard's instances are reported for this problem, which can be used as a basis of comparison in future studies.

Suggested Citation

  • Ribas, Imma & Companys, Ramon & Tort-Martorell, Xavier, 2011. "An iterated greedy algorithm for the flowshop scheduling problem with blocking," Omega, Elsevier, vol. 39(3), pages 293-301, June.
    • Handle: RePEc:eee:jomega:v:39:y:2011:i:3:p:293-301
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    4. Huerta-Muñoz, Diana L. & Ríos-Mercado, Roger Z. & Ruiz, Rubén, 2017. "An iterated greedy heuristic for a market segmentation problem with multiple attributes," European Journal of Operational Research, Elsevier, vol. 261(1), pages 75-87.
    5. 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.
    6. Pan, Quan-Ke & Ruiz, Rubén, 2012. "An estimation of distribution algorithm for lot-streaming flow shop problems with setup times," Omega, Elsevier, vol. 40(2), pages 166-180, April.
    7. Pan, Quan-Ke & Ruiz, Rubén, 2012. "Local search methods for the flowshop scheduling problem with flowtime minimization," European Journal of Operational Research, Elsevier, vol. 222(1), pages 31-43.
    8. Lozano, M. & Molina, D. & GarcI´a-MartI´nez, C., 2011. "Iterated greedy for the maximum diversity problem," European Journal of Operational Research, Elsevier, vol. 214(1), pages 31-38, October.
    9. Yu, Tae-Sun & Pinedo, Michael, 2020. "Flow shops with reentry: Reversibility properties and makespan optimal schedules," European Journal of Operational Research, Elsevier, vol. 282(2), pages 478-490.
    10. 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.
    11. Hong-Yan Sang & Quan-Ke Pan & Pei-Yong Duan & Jun-Qing Li, 2018. "An effective discrete invasive weed optimization algorithm for lot-streaming flowshop scheduling problems," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1337-1349, August.
    12. 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.
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    15. García-Martínez, C. & Rodriguez, F.J. & Lozano, M., 2014. "Tabu-enhanced iterated greedy algorithm: A case study in the quadratic multiple knapsack problem," European Journal of Operational Research, Elsevier, vol. 232(3), pages 454-463.
    16. 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.
    17. David Füßler & Stefan Fedtke & Nils Boysen, 2019. "The cafeteria problem: order sequencing and picker routing in on-the-line picking systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 727-756, September.
    18. Ansis Ozolins, 2019. "Improved bounded dynamic programming algorithm for solving the blocking flow shop problem," 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. 27(1), pages 15-38, March.
    19. 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.
    20. Marco Pranzo & Dario Pacciarelli, 2016. "An iterated greedy metaheuristic for the blocking job shop scheduling problem," Journal of Heuristics, Springer, vol. 22(4), pages 587-611, August.
    21. Nouha Nouri & Talel Ladhari, 2018. "Evolutionary multiobjective optimization for the multi-machine flow shop scheduling problem under blocking," Annals of Operations Research, Springer, vol. 267(1), pages 413-430, August.
    22. 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.
    23. Ding, Jian-Ya & Song, Shiji & Wu, Cheng, 2016. "Carbon-efficient scheduling of flow shops by multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 248(3), pages 758-771.
    24. Turabieh, Hamza & Abdullah, Salwani, 2011. "An integrated hybrid approach to the examination timetabling problem," Omega, Elsevier, vol. 39(6), pages 598-607, December.
    25. Nur Azriati Mat* & Aida Mauziah Benjamin & Syariza Abdul-Rahman, 2018. "Efficiency of Heuristic Algorithms in Solving Waste Collection Vehicle Routing Problem: A Case Study," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 695-700:6.

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