Abstract
Robust optimization has come out to be a potent approach to study mathematical problems with data uncertainty. We use robust optimization to study a nonsmooth nonconvex mathematical program over cones with data uncertainty containing generalized convex functions. We study sufficient optimality conditions for the problem. Then we construct its robust dual problem and provide appropriate duality theorems which show the relation between uncertainty problems and their corresponding robust dual problems.
| Original language | English |
|---|---|
| Pages (from-to) | 2181-2188 |
| Number of pages | 8 |
| Journal | RAIRO - Operations Research |
| Volume | 55 |
| Issue number | 4 |
| DOIs | |
| State | Published - 1 Jul 2021 |
Bibliographical note
Publisher Copyright:© The authors. Published by EDP Sciences, ROADEF, SMAI 2021.
Keywords
- Generalized convexity
- Robust duality
- Robust nonsmooth optimization
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science Applications
- Management Science and Operations Research
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