Mathematical Programming: Series A and B
A variable dimension solution approach for the general spatial price equilibrium problem
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
Product positioning under price competition
Management Science
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
A new polynomial time method for a linear complementarity problem
Mathematical Programming: Series A and B
A nonsmooth Newton method for variational inequalities, I: theory
Mathematical Programming: Series A and B
A nonsmooth Newton method for variational inequalities, II: numerical results
Mathematical Programming: Series A and B
New variants of bundle methods
Mathematical Programming: Series A and B
A unifying geometric solution framework and complexity analysis for variational inequalities
Mathematical Programming: Series A and B
Modified Projection-Type Methods for Monotone Variational Inequalities
SIAM Journal on Control and Optimization
Pseudomonotone variational inequality problems: existence of solutions
Mathematical Programming: Series A and B
Averaging schemes for variational inequalities and systems of equations
Mathematics of Operations Research
Interior point algorithms: theory and analysis
Interior point algorithms: theory and analysis
A combined relaxation method for variational inequalities with nonlinear constraints
Mathematical Programming: Series A and B
Complexity Analysis of an Interior Cutting Plane Method for Convex Feasibility Problems
SIAM Journal on Optimization
An analytic center cutting plane method for pseudomonotone variational inequalities
Operations Research Letters
Solving variational inequalities with a quadratic cut method: a primal-dual, Jacobian-free approach
Computers and Operations Research
Pseudomonotone$${_{\ast}}$$ maps and the cutting plane property
Journal of Global Optimization
Using ACCPM in a simplicial decomposition algorithm for the traffic assignment problem
Computational Optimization and Applications
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We present an algorithm for variational inequalities VI({\cal F}, Y)that uses a primal-dual version of the Analytic Center Cutting PlaneMethod.The point-to-set mapping {\cal F} is assumed to be monotone, orpseudomonotone. Each computation of a new analytic center requiresat most four Newton iterations, in theory, and in practiceone or sometimes two. Linear equalities that may be included in the definitionof the set Y are taken explicitly into account.We report numerical experiments on several well—known variational inequalityproblems as well as on one where the functional results from thesolution of large subproblems. The method is robust and competitive withalgorithms which use the same information as this one.