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A one-step tabu search algorithm for manufacturing cell design

Author

Listed:
  • S Lozano

    (Universidad de Sevilla)

  • B Adenso-Díaz

    (Universidad de Oviedo)

  • I Eguia

    (Universidad de Sevilla)

  • L Onieva

    (Universidad de Sevilla)

Abstract

As part of the cellular manufacturing design process, machines must be grouped in cells and the corresponding part families must be assigned. Limits on both the number of machines per cell and the number of parts per family can be considered. A weighted sum of intracell voids and intercellular moves is used to evaluate the quality of the solutions. We present a tabu search algorithm that systematically explores feasible machine cells configurations determining the corresponding part families using a linear network flow model. The performance of this tabu search is benchmarked against two simulated annealing approaches, another tabu search approach and three heuristics: (ZODIAC, GRAFICS and MST).

Suggested Citation

  • S Lozano & B Adenso-Díaz & I Eguia & L Onieva, 1999. "A one-step tabu search algorithm for manufacturing cell design," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(5), pages 509-516, May.
    • Handle: RePEc:pal:jorsoc:v:50:y:1999:i:5:d:10.1057_palgrave.jors.2600704
    DOI: 10.1057/palgrave.jors.2600704
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    Citations

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    Cited by:

    1. Sheu Chen, 2010. "A Heuristic Algorithm for Hierarchical Hub-and-spoke Network of Time-definite Common Carrier Operation Planning Problem," Networks and Spatial Economics, Springer, vol. 10(4), pages 509-523, December.
    2. R Torres-Velázquez & V Estivill-Castro, 2004. "Local search for Hamiltonian Path with applications to clustering visitation paths," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(7), pages 737-748, July.
    3. Ricardo Soto & Broderick Crawford & Rodrigo Olivares & César Carrasco & Eduardo Rodriguez-Tello & Carlos Castro & Fernando Paredes & Hanns de la Fuente-Mella, 2020. "A Reactive Population Approach on the Dolphin Echolocation Algorithm for Solving Cell Manufacturing Systems," Mathematics, MDPI, vol. 8(9), pages 1-25, August.
    4. Jose Joaquin del Pozo-Antúnez & Francisco Fernández-Navarro & Horacio Molina-Sánchez & Antonio Ariza-Montes & Mariano Carbonero-Ruz, 2021. "The Machine-Part Cell Formation Problem with Non-Binary Values: A MILP Model and a Case of Study in the Accounting Profession," Mathematics, MDPI, vol. 9(15), pages 1-16, July.
    5. Boutsinas, Basilis, 2013. "Machine-part cell formation using biclustering," European Journal of Operational Research, Elsevier, vol. 230(3), pages 563-572.
    6. Yin, Yong & Yasuda, Kazuhiko, 2006. "Similarity coefficient methods applied to the cell formation problem: A taxonomy and review," International Journal of Production Economics, Elsevier, vol. 101(2), pages 329-352, June.
    7. Papaioannou, Grammatoula & Wilson, John M., 2010. "The evolution of cell formation problem methodologies based on recent studies (1997-2008): Review and directions for future research," European Journal of Operational Research, Elsevier, vol. 206(3), pages 509-521, November.
    8. Belarmino Adenso-Díaz & Manuel Laguna, 2006. "Fine-Tuning of Algorithms Using Fractional Experimental Designs and Local Search," Operations Research, INFORMS, vol. 54(1), pages 99-114, February.

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