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A Survey of Meta-Heuristics used for Computing Maximin Latin Hypercube

Abstract : Finding maximin latin hypercube is a discrete optimization problem considered 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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Contributor : Elodie Dubrac <>
Submitted on : Friday, January 10, 2014 - 10:38:18 AM
Last modification on : Friday, August 27, 2021 - 3:32:48 AM


  • HAL Id : hal-00926729, version 1



Arpad Rimmel, Fabien Teytaud. A Survey of Meta-Heuristics used for Computing Maximin Latin Hypercube. EvoCOP 2014, Apr 2014, Grenade, Spain. 12 p. ⟨hal-00926729⟩



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