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Evolutionary Optimization of Low-Discrepancy Sequences

François-Michel De Rainville, Christian Gagné, Olivier Teytaud and Denis Laurendeau
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Abstract - Low-discrepancy sequences provide a way to generate quasi-random numbers of high dimensionality with a very high level of uniformity. The nearly orthogonal Latin hypercube and the generalized Halton sequence are two popular methods when it comes to generate low-discrepancy sequences. In this article, we propose to use evolutionary algorithms in order to find optimized solutions to the combinatorial problem of configuring generators of these sequences. Experimental results show that the optimized sequence generators behave at least as well as generators from the literature for the Halton sequence and significantly better for the nearly orthogonal Latin hypercube.

Bibtex:

@article{Rainville933,
author    = { François-Michel De Rainville and Christian Gagné and Olivier Teytaud and Denis Laurendeau },
title     = { Evolutionary Optimization of Low-Discrepancy Sequences },
volume    = { 22 },
number    = { 2 },
pages     = { 9:1--9:25 },
year      = { 2012 },
note      = { ACM Authorizer link http://dl.acm.org/authorize?6755981 },
journal   = { ACM Transactions on Modeling and Computer Simulation },
web       = { http://dl.acm.org/authorize?6755981 }
}

Dernière modification: 2012/04/17 par fmder1

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