D.C. programming approach to generalized Nash equilibrium with quadratic objective functions
Abstract
In this paper, we present a new approach for solving the generalized Nash equilibrium problem (GNEP), where players have nonconvex quadratic objective functions and are subject to jointly convex shared constraints. We showed that this problem can be reformulated as a nonconvex unconstrained optimization problem based on a regularized Nikaido-Isoda function. This reformulation reduces to a difference of two convex functions (D.C.) programming problem, which enables us to apply local and global search methods developed in A. S. Strekalovsky. Numerical results are presented.
Fields of Study & Subjects
Optimization and Variational Analysis
Advanced Optimization Algorithms Research
Adaptive Dynamic Programming Control
Publication details
- Journal / source
- Journal of Industrial and Management Optimization
- Volume
- 22
- Issue
- 2
- Pages
- 860–879
- Publication date
- 1 January 2026