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Evaluation of the Simulated Annealing and the Discrete Artificial Bee Colony in the Weight Tardiness Problem with Taguchi Experiments Parameterization

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Intelligent Systems Design and Applications (ISDA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 557))

Abstract

Meta-Heuristics (MH) are the most used optimization techniques to approach Complex Combinatorial Problems (COPs). Their ability to move beyond the local optimums make them an especially attractive choice to solve complex computational problems, such as most scheduling problems. However, the knowledge of what Meta-Heuristics perform better in certain problems is based on experiments. Classic MH, as the Simulated Annealing (SA) has been deeply studied, but newer MH, as the Discrete Artificial Bee Colony (DABC) still need to be examined in more detail. In this paper DABC has been compared with SA in 30 academic benchmark instances of the weighted tardiness problem (1||Σw j T j ). Both MH parameters were fine-tuned with Taguchi Experiments. In the computational study DABC performed better and the subsequent statistical study demonstrated that DABC is more prone to find near-optimum solutions. On the other hand SA appeared to be more efficient.

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Acknowledgments

This work is supported by FEDER Funds through the “Programa Operacional Factores de Competitividade - COMPETE” program and by National Funds through FCT “Fundação para a Ciência e a Tecnologia” under the project: PEst-OE/EEI/UI0760/2014, and PEst2015-2020.

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Authors and Affiliations

  1. School of Engineering - Department of Production and Systems, University of Minho, Guimarães, Portugal

    André S. Santos & Maria R. Varela

  2. School of Engineering - GECAD Research Group, Polytechnic Institute of Porto, Porto, Portugal

    Ana M. Madureira

Authors
  1. André S. Santos
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  2. Ana M. Madureira
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  3. Maria R. Varela
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Corresponding author

Correspondence to Maria R. Varela .

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Editors and Affiliations

  1. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  3. Polytechnic Institute of Porto, Felgueiras, Portugal

    Dorabela Gamboa

  4. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

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Santos, A.S., Madureira, A.M., Varela, M.R. (2017). Evaluation of the Simulated Annealing and the Discrete Artificial Bee Colony in the Weight Tardiness Problem with Taguchi Experiments Parameterization. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_71

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  • DOI: https://doi.org/10.1007/978-3-319-53480-0_71

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53479-4

  • Online ISBN: 978-3-319-53480-0

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