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.


Genetic Algorithm Simulated Annealing Mutation Operator Discrete Optimization Problem Iterate Local Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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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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