Arnaldo S. Brito

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In this paper, we propose an algorithm for solving multiobjective minimization problems on nonempty closed convex subsets of the Euclidean space. The proposed method combines a reflection technique for obtaining a feasible point with a projected subgradient method. Under suitable assumptions, we show that the sequence generated using this method converges(More)
In this paper, we consider the problem of general equilibrium in a finite-dimensional space on a closed convex set. For solving this problem, we developed an interior proximal point algorithm with φ-divergence. Under reasonable assumptions, we prove that the sequence generated by the algorithm converges to a solution of the Equilibrium Problem, when the(More)
In this paper, we proposed algorithms interior proximal methods based on entropylike distance for the minimization of the quasiconvex function subjected to nonnegativity constraints. Under the assumptions that the objective function is bounded below and continuously differentiable, we established the well definedness of the sequence generated by the(More)
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