|Start Page Number:||597|
|End Page Number:||614|
|Publication Date:||Jul 2016|
|Journal:||Journal of Global Optimization|
|Authors:||Cruz J, Milln R|
|Keywords:||heuristics, programming: convex|
We introduce a relaxed‐projection splitting algorithm for solving variational inequalities in Hilbert spaces for the sum of nonsmooth maximal monotone operators, where the feasible set is defined by a nonlinear and nonsmooth continuous convex function inequality. In our scheme, the orthogonal projections onto the feasible set are replaced by projections onto separating hyperplanes. Furthermore, each iteration of the proposed method consists of simple subgradient‐like steps, which does not demand the solution of a nontrivial subproblem, using only individual operators, which exploits the structure of the problem. Assuming monotonicity of the individual operators and the existence of solutions, we prove that the generated sequence converges weakly to a solution.