Derivative-free robust optimization by outer approximations

Menickelly, Matt; Wild, Stefan M.

doi:10.1007/s10107-018-1326-9

Title: Derivative-free robust optimization by outer approximations

Journal Article · Fri Oct 26 00:00:00 EDT 2018 · Mathematical Programming

DOI:https://doi.org/10.1007/s10107-018-1326-9· OSTI ID:1631967

^[1]; Wild, Stefan M. ^[1]

Argonne National Lab. (ANL), Argonne, IL (United States). Mathematics and Computer Science Division

We develop an algorithm for minimax problems that arise in robust optimization in the absence of objective function derivatives. The algorithm utilizes an extension of methods for inexact outer approximation in sampling a potentially infinite-cardinality uncertainty set. Clarke stationarity of the algorithm output is established alongside desirable features of the model-based trust-region subproblems encountered. We demonstrate the practical benefits of the algorithm on a new class of test problems.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1631967

Journal Information:: Mathematical Programming, Vol. 179, Issue 1-2; ISSN 0025-5610

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 15 works

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