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Lectures on Parametric Optimization: An Introduction

Georg Still(g.j.still***at***utwente.nl )

Abstract: The report aims to provide an overview over results from Parametric Optimization which could be called classical results on the subject. Parametric Optimization considers optimization problems depending on a parameter and describes how the feasible set, the value function, and the local or global minimizers of the program depend on changes in the parameter. After an introduction into nonparametric programs the report deals with stability results for linear, convex, and nonlinear parametric programs. As one of the applications, mathematical programs arising in models from traffic engineering are investigated. To facilitate the accessibility of the report to a broader group of mathematicians and engineers, the exposition contains many example problems.

Keywords: parametric optimization, nonlinear optimization, sensitivity and stability results

Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )

Category 2: Convex and Nonsmooth Optimization (Convex Optimization )

Citation: Preprint, University of Twente, March 2018

Download: [PDF]

Entry Submitted: 04/23/2018
Entry Accepted: 04/23/2018
Entry Last Modified: 04/23/2018

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