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Two-Stage Nested Partitions Method for Stochastic Optimization

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  • Sigurdur Ólafsson

    (Iowa State University)

Abstract

We address the problem of optimizing over a large but finite set when the objective function does not have an analytical expression and is evaluated using noisy estimation. Building on the recently proposed nested partitions method for stochastic optimization, we develop a new approach that combines this random search method and statistical selection for guiding the search. We prove asymptotic convergence and analyze the finite time behavior of the new approach. We also report extensive numerical results to illustrate the benefits of the new approach.

Suggested Citation

  • Sigurdur Ólafsson, 2004. "Two-Stage Nested Partitions Method for Stochastic Optimization," Methodology and Computing in Applied Probability, Springer, vol. 6(1), pages 5-27, March.
    • Handle: RePEc:spr:metcap:v:6:y:2004:i:1:d:10.1023_b:mcap.0000012413.54789.cc
    DOI: 10.1023/B:MCAP.0000012413.54789.cc
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    References listed on IDEAS

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    1. Sidney Yakowitz & Pierre L'Ecuyer & Felisa Vázquez-Abad, 2000. "Global Stochastic Optimization with Low-Dispersion Point Sets," Operations Research, INFORMS, vol. 48(6), pages 939-950, December.
    2. Reuven Rubinstein, 1999. "The Cross-Entropy Method for Combinatorial and Continuous Optimization," Methodology and Computing in Applied Probability, Springer, vol. 1(2), pages 127-190, September.
    3. Vladimir I. Norkin & Yuri M. Ermoliev & Andrzej Ruszczyński, 1998. "On Optimal Allocation of Indivisibles Under Uncertainty," Operations Research, INFORMS, vol. 46(3), pages 381-395, June.
    4. Frank J. Matejcik & Barry L. Nelson, 1995. "Two-Stage Multiple Comparisons with the Best for Computer Simulation," Operations Research, INFORMS, vol. 43(4), pages 633-640, August.
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    Cited by:

    1. Zdravko I. Botev & Dirk P. Kroese, 2008. "An Efficient Algorithm for Rare-event Probability Estimation, Combinatorial Optimization, and Counting," Methodology and Computing in Applied Probability, Springer, vol. 10(4), pages 471-505, December.

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