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Zbl 0565.90058
Spingarn, Jonathan E.
Applications of the method of partial inverses to convex programming: Decomposition. (English)
[J] Math. Program. 32, 199-223 (1985). ISSN 0025-5610; ISSN 1436-4646/e

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 2000:: *90C25 Convex programming
90C55 Methods of successive quadratic programming type
65K05 Mathematical programming (numerical methods)
90C06 Large-scale problems

Keywords: primal-dual decomposition method; separable convex programming; proximal point algorithm; monotone multifunction; linear convergence

Cited in: Zbl 1122.90061

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