Sensitivity analysis for parametric nonlinear programming: A tutorial

Fuente: arXiv
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Main Author: Pacaud, François
Format: Preprint
Published: 2025
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author Pacaud, François
author_facet Pacaud, François
contents This tutorial provides an overview of the current state-of-the-art in the sensitivity analysis for nonlinear programming. Building upon the fundamental work of Fiacco, it derives the sensitivity of primal-dual solutions for regular nonlinear programs and explores the extent to which Fiacco's framework can be extended to degenerate nonlinear programs with non-unique dual solutions. The survey ends with a discussion on how to adapt the sensitivity analysis for conic programs and approximate solutions obtained from interior-point algorithms.
format Preprint
id arxiv_https___arxiv_org_abs_2504_15851
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Sensitivity analysis for parametric nonlinear programming: A tutorial
Pacaud, François
Optimization and Control
This tutorial provides an overview of the current state-of-the-art in the sensitivity analysis for nonlinear programming. Building upon the fundamental work of Fiacco, it derives the sensitivity of primal-dual solutions for regular nonlinear programs and explores the extent to which Fiacco's framework can be extended to degenerate nonlinear programs with non-unique dual solutions. The survey ends with a discussion on how to adapt the sensitivity analysis for conic programs and approximate solutions obtained from interior-point algorithms.
title Sensitivity analysis for parametric nonlinear programming: A tutorial
topic Optimization and Control
url https://arxiv.org/abs/2504.15851