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Optimization with hidden constraints and embedded Monte Carlo computations
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.
Optimization with hidden constraints and embedded Monte Carlo computations
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.
Optimization with hidden constraints and embedded Monte Carlo computations
Chen, Xiaojun (author) / Kelley, C. T. (author)
Optimization and Engineering ; 17 ; 157-175
2015-12-22
19 pages
Article (Journal)
Electronic Resource
English
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