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Two-level primal-dual proximal decomposition technique to solve large scale optimization problems. (English) Zbl 1122.90061
Summary: We describe a primal-dual application of the proximal point algorithm to nonconvex minimization problems. Motivated by the work of J. E. Spingarn [Math. Program. 32, 199–223 (1985; Zbl 0565.90058)] and more recently by the work of A. Hamdi et al. [Lect. Notes Econ. Math. Syst. 452, 90–104 (1997; Zbl 0882.65055)] about the primal resource-directive decomposition scheme to solve nonlinear separable problems. This paper discusses some local results of a primal-dual regularization approach that leads to a decomposition algorithm.
90C26Nonconvex programming, global optimization