DocumentCode
333198
Title
Average performance of quasi Monte Carlo methods for global optimization
Author
Al-Mharmah, Hisham A.
Author_Institution
Dept. of Ind. Eng., Jordan Univ., Amman, Jordan
Volume
1
fYear
1998
fDate
13-16 Dec 1998
Firstpage
623
Abstract
We compare the average performance of one class of low-discrepancy quasi-Monte Carlo sequences for global optimization. The Weiner measure is assumed as the prior probability on all optimized functions. We show how to construct van der Corput sequences and we prove their consistency. Numerical experimentation shows that the van der Corput sequence in base 2 has a better average performance
Keywords
Monte Carlo methods; integration; mathematical programming; Weiner measure; average performance; global optimization; numerical integration; numerical method; prior; prior probability; quasi Monte Carlo methods; random sampling; van der Corput sequences; Approximation error; Error analysis; Industrial engineering; Monte Carlo methods; Optimization methods; Sampling methods; Terminology;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference Proceedings, 1998. Winter
Conference_Location
Washington, DC
Print_ISBN
0-7803-5133-9
Type
conf
DOI
10.1109/WSC.1998.745043
Filename
745043
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