Mathematical Programming: Series A and B
A unifying geometric solution framework and complexity analysis for variational inequalities
Mathematical Programming: Series A and B
Complexity analysis of the analytic center cutting plane method that uses multiple cuts
Mathematical Programming: Series A and B
Computational Optimization and Applications
Complexity Analysis of an Interior Cutting Plane Method for Convex Feasibility Problems
SIAM Journal on Optimization
Homogeneous Analytic Center Cutting Plane Methods for Convex Problems and Variational Inequalities
SIAM Journal on Optimization
Multiple Cuts in the Analytic Center Cutting Plane Method
SIAM Journal on Optimization
An Analytic Center Based Column Generation Algorithm for Convex Quadratic Feasibility Problems
SIAM Journal on Optimization
The Analytic Center Quadratic Cut Method for Strongly Monotone Variational Inequality Problems
SIAM Journal on Optimization
Analysis of a Cutting Plane Method That Uses Weighted Analytic Center and Multiple Cuts
SIAM Journal on Optimization
A Cutting Plane Method for Solving Quasimonotone Variational Inequalities
Computational Optimization and Applications
An analytic center cutting plane method for pseudomonotone variational inequalities
Operations Research Letters
Solving variational inequalities defined on a domain with infinitely many linear constraints
Computational Optimization and Applications
On saddle points in nonconvex semi-infinite programming
Journal of Global Optimization
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We study a variational inequality problem VI(X,F) with X being defined by infinitely many inequality constraints and F being a pseudomonotone function. It is shown that such problem can be reduced to a problem of finding a feasible point in a convex set defined by infinitely many constraints. An analytic center based cutting plane algorithm is proposed for solving the reduced problem. Under proper assumptions, the proposed algorithm finds an ε-optimal solution in O*(n2/ρ2) iterations, where O*(·) represents the leading order, n is the dimension of X, ϵ is a user-specified tolerance, and ρ is the radius of a ball contained in the ϵ-solution set of VI(X,F).