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Revisiting the Simulated Annealing Algorithm from a Teaching Perspective

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International Joint Conference SOCO’16-CISIS’16-ICEUTE’16 (SOCO 2016, CISIS 2016, ICEUTE 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 527))

Abstract

Hill climbing and simulated annealing are two fundamental search techniques integrating most artificial intelligence and machine learning courses curricula. These techniques serve as introduction to stochastic and probabilistic based metaheuristics. Simulated annealing can be considered a hill-climbing variant with a probabilistic decision. While simulated annealing is conceptually a simple algorithm, in practice it can be difficult to parameterize. In order to promote a good simulated annealing algorithm perception by students, a simulation experiment is reported here. Key implementation issues are addressed, both for minimization and maximization problems. Simulation results are presented.

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Authors and Affiliations

  1. Department of Engineering, School of Sciences and Technology, INESC TEC – INESC Technology and Science, 5001–801, Vila Real, Portugal

    Paulo B. de Moura Oliveira & Eduardo J. Solteiro Pires

  2. Centro ALGORITMI/Departamento de Informática, Universidade do Minho, Braga, Portugal

    Paulo Novais

Authors
  1. Paulo B. de Moura Oliveira
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  2. Eduardo J. Solteiro Pires
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  3. Paulo Novais
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Corresponding author

Correspondence to Paulo B. de Moura Oliveira .

Editor information

Editors and Affiliations

  1. Computational Intelligence Group, University of the Basque Country (UPV/EHU), San Sebastian, Spain

    Manuel Graña

  2. University of the Basque Country, Vitoria, Spain

    José Manuel López-Guede

  3. Computational Intelligence Group, University of the Basque Country (UPV/EHU), San Sebastian, Spain

    Oier Etxaniz

  4. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  5. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  6. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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de Moura Oliveira, P.B., Pires, E.J.S., Novais, P. (2017). Revisiting the Simulated Annealing Algorithm from a Teaching Perspective. In: Graña, M., López-Guede, J.M., Etxaniz, O., Herrero, Á., Quintián, H., Corchado, E. (eds) International Joint Conference SOCO’16-CISIS’16-ICEUTE’16. SOCO CISIS ICEUTE 2016 2016 2016. Advances in Intelligent Systems and Computing, vol 527. Springer, Cham. https://doi.org/10.1007/978-3-319-47364-2_70

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  • DOI: https://doi.org/10.1007/978-3-319-47364-2_70

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47363-5

  • Online ISBN: 978-3-319-47364-2

  • eBook Packages: EngineeringEngineering (R0)

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