A Survey of Meta-heuristics Used for Computing Maximin Latin Hypercube

  • Arpad Rimmel
  • Fabien Teytaud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8600)


Finding maximin latin hypercube is a discrete optimization problem believed to be NP-hard. In this paper, we compare different meta-heuristics used to tackle this problem: genetic algorithm, simulated annealing and iterated local search. We also measure the importance of the choice of the mutation operator and the evaluation function. All the experiments are done using a fixed number of evaluations to allow future comparisons. Simulated annealing is the algorithm that performed the best. By using it, we obtained new highscores for a very large number of latin hypercubes.




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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Arpad Rimmel
    • 1
  • Fabien Teytaud
    • 2
  1. 1.Supélec E3SFrance
  2. 2.Univ. Lille Nord de FranceFrance

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