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Revisiting the Simulated Annealing Algorithm from a Teaching Perspective

  • Paulo B. de Moura OliveiraEmail author
  • Eduardo J. Solteiro Pires
  • Paulo Novais
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (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.

Keywords

Simulated annealing Meta-heuristics Artificial intelligence education 

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Authors and Affiliations

  • Paulo B. de Moura Oliveira
    • 1
    Email author
  • Eduardo J. Solteiro Pires
    • 1
  • Paulo Novais
    • 2
  1. 1.Department of Engineering, School of Sciences and TechnologyINESC TEC – INESC Technology and ScienceVila RealPortugal
  2. 2.Centro ALGORITMI/Departamento de InformáticaUniversidade do MinhoBragaPortugal

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