Abstract
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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Rimmel, A., Teytaud, F. (2014). A Survey of Meta-heuristics Used for Computing Maximin Latin Hypercube. In: Blum, C., Ochoa, G. (eds) Evolutionary Computation in Combinatorial Optimisation. EvoCOP 2014. Lecture Notes in Computer Science, vol 8600. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44320-0_3
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DOI: https://doi.org/10.1007/978-3-662-44320-0_3
Publisher Name: Springer, Berlin, Heidelberg
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