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Applications of the method of partial inverses to convex programming: Decomposition. (English) Zbl 0565.90058
A primal-dual decomposition method is presented to solve the separable convex programming problem. Convergence to a solution and Lagrange multiplier vector occurs from an arbitrary starting point. The method is equivalent to the proximal point algorithm applied to a certain maximal monotone multifunction. In the nonseparable case, it specializes to a known method, the proximal method of multipliers. Conditions are provided which guarantee linear convergence.

MSC:
90C25Convex programming
90C55Methods of successive quadratic programming type
65K05Mathematical programming (numerical methods)
90C06Large-scale problems (mathematical programming)
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