Scenario Approximation of Robust and Chance-Constrained Programs

Abstract

We consider scenario approximation of problems given by the optimization of a function over a constraint that is too difficult to be handled but can be efficiently approximated by a finite collection of constraints corresponding to alternative scenarios. The covered programs include min-max games, and semi-infinite, robust and chance-constrained programming problems. We prove convergence of the solutions of the approximated programs to the given ones, using mainly epigraphical convergence, a kind of variational convergence that has demonstrated to be a valuable tool in optimization problems.

Publication
Journal of Optimization Theory and Applications, 158(2), 590-614

Raffaello Seri
Raffaello Seri
Professor of Econometrics

My research interests include statistics, numerical analysis, operations research, psychology, economics and management.

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