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Nonconvex Quasi-Variational Inequalities: Stability Analysis and Application to Numerical Optimization

Published: 06 January 2025 Publication History

Abstract

We consider a parametric quasi-variational inequality (QVI) without any convexity assumption. Using the concept of optimal value function, we transform the problem into that of solving a nonsmooth system of inequalities. Based on this reformulation, new coderivative estimates as well as robust stability conditions for the optimal solution map of this QVI are developed. Also, for an optimization problem with QVI constraint, necessary optimality conditions are constructed and subsequently, a tailored semismooth Newton-type method is designed, implemented, and tested on a wide range of optimization examples from the literature. In addition to the fact that our approach does not require convexity, its coderivative and stability analysis do not involve second order derivatives, and subsequently, the proposed Newton scheme does not need third order derivatives, as it is the case for some previous works in the literature.

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Published In

cover image Journal of Optimization Theory and Applications
Journal of Optimization Theory and Applications  Volume 204, Issue 2
Feb 2025
527 pages

Publisher

Plenum Press

United States

Publication History

Published: 06 January 2025
Accepted: 23 October 2024
Received: 19 February 2023

Author Tags

  1. Quasi-variational inequalities
  2. Stability analysis
  3. Optimal value function
  4. Optimization problems with quasi-variational inequality constraints
  5. Semismooth Newton method

Author Tags

  1. 90C26
  2. 90C31
  3. 90C33
  4. 90C46
  5. 90C55

Author Tag

  1. Mathematical Sciences
  2. Numerical and Computational Mathematics

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