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Metaheuristics for the template design problem: encoding, symmetry and hybridisation

Author

Listed:
  • David Rodríguez Rueda

    (Universidad Nacional Experimental del Táchira (UNET))

  • Carlos Cotta

    (Universidad de Málaga)

  • Antonio J. Fernández-Leiva

    (Universidad de Málaga)

Abstract

The template design problem (TDP) is a hard combinatorial problem with a high number of symmetries which makes solving it more complicated. A number of techniques have been proposed in the literature to optimise its resolution, ranging from complete methods to stochastic ones. However, although metaheuristics are considered efficient methods that can find enough-quality solutions at a reasonable computational cost, these techniques have not proven to be truly efficient enough to deal with this problem. This paper explores and analyses a wide range of metaheuristics to tackle the problem with the aim of assessing their suitability for finding template designs. We tackle the problem using a wide set of metaheuristics whose implementation is guided by a number of issues such as problem formulation, solution encoding, the symmetrical nature of the problem, and distinct forms of hybridisation. For the TDP, we also propose a slot-based alternative problem formulation (distinct to other slot-based proposals), which represents another option other than the classical variation-based formulation of the problem. An empirical analysis, assessing the performance of all the metaheuristics (i.e., basic, integrative and collaborative algorithms working on different search spaces and with/without symmetry breaking) shows that some of our proposals can be considered the state-of-the-art when they are applied to specific problem instances.

Suggested Citation

  • David Rodríguez Rueda & Carlos Cotta & Antonio J. Fernández-Leiva, 2021. "Metaheuristics for the template design problem: encoding, symmetry and hybridisation," Journal of Intelligent Manufacturing, Springer, vol. 32(2), pages 559-578, February.
  • Handle: RePEc:spr:joinma:v:32:y:2021:i:2:d:10.1007_s10845-020-01587-w
    DOI: 10.1007/s10845-020-01587-w
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    References listed on IDEAS

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    1. James T. Lin & Chun-Chih Chiu, 2018. "A hybrid particle swarm optimization with local search for stochastic resource allocation problem," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 481-495, March.
    2. S. Prestwich, 2003. "Negative Effects of Modeling Techniques on Search Performance," Annals of Operations Research, Springer, vol. 118(1), pages 137-150, February.
    3. Les Proll & Barbara Smith, 1998. "Integer Linear Programming and Constraint Programming Approaches to a Template Design Problem," INFORMS Journal on Computing, INFORMS, vol. 10(3), pages 265-275, August.
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