Second-Order Optimality Conditions for Bilevel Optimization Problems Using Parabolic Directional Derivatives

This paper studies the second-order properties of a class of inequality-constrained bilevel programming problems. First-order optimality conditions for the existence of solutions to bilevel optimization problems are derived using the first-order directional derivative of the optimal solution function of the lower-level problem in the seminal paper by Dempe (1992). In this work, we prove that … Read more

Convergence of the Frank-Wolfe Algorithm for Monotone Variational Inequalities

We consider the Frank-Wolfe algorithm for solving variational inequalities over compact, convex sets under a monotone \(C^1\) operator and vanishing, nonsummable step sizes. We introduce a continuous-time interpolation of the discrete iteration and use tools from dynamical systems theory to analyze its asymptotic behavior. This allows us to derive convergence results for the original discrete … Read more

Chance-Constrained Linear Complementarity Problems

We study linear complementarity problems (LCPs) under uncertainty, which we model using chance constraints. Since the complementarity condition of the LCP is an equality constraint, it is required to consider relaxations, which naturally leads to optimization problems in which the relaxation parameters are minimized for given probability levels. We focus on these optimization problems and … Read more

Efficient Warm-Start Strategies for Nash-based Linear Complementarity Problems via Bilinear Approximation

We present an effective warm-starting scheme for solving large linear complementarity problems (LCPs) arising from Nash equilibrium problems. The approach generates high-quality starting points that, when passed to the PATH solver, yield substantial reductions in computational time and variance. Our warm-start routine reformulates each agent’s LP using strong duality, leading to a master problem with … Read more

A General Penalty-Method and a General Regularization-Method for Cardinality-Constrained Optimization Problems

We consider cardinality-constrained optimization problems (CCOPs), which are general nonlinear programs with an additional constraint limiting the number of nonzero continuous variables. The continuous reformulation of CCOPs involves complementarity constraints, which pose significant theoretical and computational challenges. To address these difficulties, we propose and analyze two numerical solution approaches: a general penalty method and a … Read more

Stability analysis of parameterized models relative to nonconvex constraints

For solution mappings of parameterized models (such as optimization problems, variational inequalities, and generalized equations), standard stability inevitably fails as the parameter approaches the boundary of the feasible domain. One remedy is relative stability restricted to a constraint set (e.g., the feasible domain), which is our focus in this paper. We establish generalized differentiation criteria … Read more

A Heuristic for Complementarity Problems Using Difference of Convex Functions

We present a new difference of convex functions algorithm (DCA) for solving linear and nonlinear mixed complementarity problems (MCPs). The approach is based on the reformulation of bilinear complementarity constraints as difference of convex (DC) functions, more specifically, the difference of scalar, convex quadratic terms. This reformulation gives rise to a DC program, which is … Read more

A linearly convergent algorithm for variational inequalities based on fiber bundle

The variational inequality (VI) problem is a fundamental mathematical framework for many classical problems. This paper introduces an algorithm that applies to arbitrary finite-dimensional VIs with general compact convex sets and general continuous functions. The algorithm guarantees global linear convergence to an approximate solution without requiring any assumptions, including the typical monotonicity. Our approach adapts … Read more

On the convergence rate of the Douglas-Rachford splitting algorithm

This work is concerned with the convergence rate analysis of the Dou- glas–Rachford splitting (DRS) method for finding a zero of the sum of two maximally monotone operators. We obtain an exact rate of convergence for the DRS algorithm and demonstrate its sharpness in the setting of convex feasibility problems. Further- more, we investigate the … Read more

Second order directional derivative of optimal solution function in parametric programming problem

In this paper, the second-order directional derivative of the optimal value function and the optimal solution function are obtained for a strongly stable parametric problem with non-unique Lagrange multipliers. Some properties of the Lagrange multipliers are proved. It is justified that the second-order directional derivative of the optimal solution function for the parametric problem can … Read more