Derivative-Free Robust Optimization By Outer Approximations

Event Sponsor: 
Mathmatics and Computer Science Division Seminar - LANS
Start Date: 
Jun 13 2018 - 10:30am
Building 240/Room 1404-1405
Argonne National Laboratory
Stefan Wild
Speaker(s) Title: 
Argonne National Laboratory, MCS

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. Joint work with Matt Menickelly.

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