Extensions of stochastic optimization results to problems with system failure probability functions

被引：27

作者：

Royset, J. O. ^{[1
]}

Polak, E.

机构：

[1] USN, Postgrad Sch, Dept Operat Res, Monterey, CA 93940 USA

[2] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 2007年 / 133卷 / 01期

关键词：

stochastic optimization; sample average approximations; Monte Carlo simulation; reliability-based optimal design;

D O I：

10.1007/s10957-007-9178-0

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We derive an implementable algorithm for solving nonlinear stochastic optimization problems with failure probability constraints using sample average approximations. The paper extends prior results dealing with a failure probability expressed by a single measure to the case of failure probability expressed in terms of multiple performance measures. We also present a new formula for the failure probability gradient. A numerical example addressing the optimal design of a reinforced concrete highway bridge illustrates the algorithm.

引用

页码：1 / 18

页数：18

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