Optimization with hidden constraints and embedded Monte Carlo computations

Xiaojun Chen; C. T. Kelley

doi:10.1007/s11081-015-9302-1

Optimization with hidden constraints and embedded Monte Carlo computations

Xiaojun Chen, C. T. Kelley

Research output: Journal article publication › Journal article › Academic research › peer-review

12 Citations (Scopus)

Abstract

In this paper we explore the convergence properties of deterministic direct search methods when the objective function contains a stochastic or Monte Carlo simulation. We present new results for the case where the objective is only defined on a set with certain minimal regularity properties. We present two numerical examples to illustrate the ideas.

Original language	English
Pages (from-to)	157-175
Number of pages	19
Journal	Optimization and Engineering
Volume	17
Issue number	1
DOIs	https://doi.org/10.1007/s11081-015-9302-1
Publication status	Published - 1 Mar 2016

Keywords

Hidden constraints
Monte Carlo simulation
Sampling methods
Water resource policy

ASJC Scopus subject areas

Software
Civil and Structural Engineering
Aerospace Engineering
Mechanical Engineering
Control and Optimization
Electrical and Electronic Engineering

More information

10.1007/s11081-015-9302-1

http://hdl.handle.net/10397/43954

Cite this

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KW - Water resource policy

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Optimization with hidden constraints and embedded Monte Carlo computations

Abstract

Keywords

ASJC Scopus subject areas

More information

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