Stabilized Sequential Quadratic Programming
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part I
Generalized Kojima–Functions and Lipschitz Stability of Critical Points
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part II
Semismooth homeomorphisms and strong stability of semidefinite and Lorentz complementarity problems
Mathematics of Operations Research
Constraint nondegeneracy in variational analysis
Mathematics of Operations Research
Coderivative Analysis of Variational Systems
Journal of Global Optimization
A General Iterative Procedure for Solving Nonsmooth Generalized Equations
Computational Optimization and Applications
Mathematics of Operations Research
Stability results for polyhedral complementarity problems
Computers & Mathematics with Applications
Necessary Optimality Conditions for Two-Stage Stochastic Programs with Equilibrium Constraints
SIAM Journal on Optimization
Real-Time Nonlinear Optimization as a Generalized Equation
SIAM Journal on Control and Optimization
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\rm Linear and nonlinear variational inequality problems over a polyhedral convex set are analyzed parametrically. Robinson's notion of strong regularity, as a criterion for the solution set to be a singleton depending Lipschitz continuously on the parameters, is characterized in terms of a new ``critical face'' condition and in other ways. The consequences for complementarity problems are worked out as a special case. Application is also made to standard nonlinear programming problems with parameters that include the canonical perturbations. In that framework a new characterization of strong regularity is obtained for the variational inequality associated with the Karush--Kuhn--Tucker conditions.