Sensitivity analysis for parametric nonlinear programming: A tutorial
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Apr 2025.
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.
- 2026dOPT: Differentiating Conic Optimization via Geometric Reduction27 Sep 2026
- 2025Sobolev Training of End-to-End Optimization Proxies16 May 2025