Nested Partitions Method for Stochastic Optimization

被引：0
|
作者：
Leyuan Shi
Sigurdur O´lafsson
机构：
[1] University of Wisconsin–Madison,Department of Industrial Engineering
[2] Iowa State University,Department of Industrial and Manufacturing Systems Engineering
来源：
Methodology And Computing In Applied Probability | 2000年 / 2卷 / 3期
关键词：
simulation-based optimization; combinatorial optimization; Markov chain Monte Carlo.;
D O I：
10.1023/A:1010081212560
中图分类号：
学科分类号：
摘要：
The nested partitions (NP) method is a recently proposed new alternative for global optimization. Primarily aimed at problems with large but finite feasible regions, the method employs a global sampling strategy that is continuously adapted via a partitioning of the feasible region. In this paper we adapt the original NP method to stochastic optimization where the performance is estimated using simulation. We prove asymptotic convergence of the new method and present a numerical example to illustrate its potential.
引用
收藏
页码：271 / 291
页数：20
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