期刊
ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION
卷 22, 期 2, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2133390.2133393
关键词
Quasi-random; Halton sequence; nearly orthogonal Latin hypercube; optimization; evolutionary algorithm
资金
- Defence Research and Development Canada Valcartier (DRDC Valcartier)
- FQRNT (Quebec)
- NSERC (Canada)
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.
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