Mathematical Programming: Series A and B
Lagrange multipliers and optimality
SIAM Review
Shadow prices for measures of effectiveness, I: linear model
Operations Research
Shadow prices for measures of effectiveness, II: general model
Operations Research
A Newton method for a class of quasi-variational inequalities
Computational Optimization and Applications
Solution Continuity in Monotone Affine Variational Inequalities
SIAM Journal on Optimization
Generalized Nash equilibrium problems and Newton methods
Mathematical Programming: Series A and B
Robinson’s implicit function theorem and its extensions
Mathematical Programming: Series A and B
Computational Optimization and Applications
On generalized Nash games and variational inequalities
Operations Research Letters
Penalty Methods for the Solution of Generalized Nash Equilibrium Problems
SIAM Journal on Optimization
Nonsmooth optimization reformulations of player convex generalized Nash equilibrium problems
Journal of Global Optimization
Nonconvex Games with Side Constraints
SIAM Journal on Optimization
A globalized Newton method for the computation of normalized Nash equilibria
Journal of Global Optimization
Sample average approximation method for a class of stochastic generalized Nash equilibrium problems
Journal of Computational and Applied Mathematics
Hi-index | 0.01 |
We consider the generalized Nash equilibrium problem (GNEP), in which each player's strategy set may depend on the rivals' strategies through shared constraints. A practical approach to solving this problem that has received increasing attention lately entails solving a related variational inequality (VI). From the viewpoint of game theory, it is important to find as many GNEs as possible, if not all of them. We propose two types of parametrized VIs related to the GNEP, one price-directed and the other resource-directed. We show that these parametrized VIs inherit the monotonicity properties of the original VI and, under mild constraint qualifications, their solutions yield all GNEs. We propose strategies to sample in the parameter spaces and show, through numerical experiments on benchmark examples, that the GNEs found by the parametrized VI approaches are widely distributed over the GNE set.