An inexact proximal point method for solving generalized fractional programs
Journal of Global Optimization
The interior proximal extragradient method for solving equilibrium problems
Journal of Global Optimization
Proximal methods for a class of bilevel monotone equilibrium problems
Journal of Global Optimization
Dual extragradient algorithms extended to equilibrium problems
Journal of Global Optimization
Iterative methods for solving monotone equilibrium problems via dual gap functions
Computational Optimization and Applications
An inexact spectral bundle method for convex quadratic semidefinite programming
Computational Optimization and Applications
Interior point methods for equilibrium problems
Computational Optimization and Applications
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We present a bundle method for solving nonsmooth convex equilibrium problems based on the auxiliary problem principle. First, we consider a general algorithm that we prove to be convergent. Then we explain how to make this algorithm implementable. The strategy is to approximate the nonsmooth convex functions by piecewise linear convex functions in such a way that the subproblems are easy to solve and the convergence is preserved. In particular, we introduce a stopping criterion which is satisfied after finitely many iterations and which gives rise to Δ-stationary points. Finally, we apply our implementable algorithm for solving the particular case of singlevalued and multivalued variational inequalities and we find again the results obtained recently by Salmon et al. [18].