Evolutionary Optimization of Low-Discrepancy Sequences

被引：27

作者：

De Rainville, Francois-Michel ^{[1
]}

Gagne, Christian ^{[1
]}

Teytaud, Olivier

Laurendeau, Denis ^{[1
]}

机构：

[1] Univ Laval, Lab Vis & Syst Numer, Dept Genie Elect & Genie Informat, Quebec City, PQ G1V 0A6, Canada

来源：

ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION | 2012年 / 22卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Quasi-random; Halton sequence; nearly orthogonal Latin hypercube; optimization; evolutionary algorithm; MONTE-CARLO METHODS; ALGORITHMS; DIMENSION; EFFICIENT; DESIGN;

D O I：

10.1145/2133390.2133393

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页数：25

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