Surrogate-based methods for black-box optimization

Ky Khac Vu; Claudia D'Ambrosio; Youssef Hamadi; Leo Liberti

doi:10.1111/itor.12292

Surrogate-based methods for black-box optimization

Ky Khac Vu
, Claudia D'Ambrosio
, Youssef Hamadi
, Leo Liberti

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, we survey methods that are currently used in black-box optimization, that is, the kind of problems whose objective functions are very expensive to evaluate and no analytical or derivative information is available. We concentrate on a particular family of methods, in which surrogate (or meta) models are iteratively constructed and used to search for global solutions.

Original language	English
Pages (from-to)	393-424
Number of pages	32
Journal	International Transactions in Operational Research
Volume	24
Issue number	3
DOIs	https://doi.org/10.1111/itor.12292
Publication status	Published - 1 May 2017

Keywords

black-box functions
heuristics
nonlinear programming
optimal control
simulation optimization

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10.1111/itor.12292

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KW - heuristics

KW - nonlinear programming

KW - optimal control

KW - simulation optimization

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Surrogate-based methods for black-box optimization

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Keywords

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