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A Proximal Multiplier Method for Convex Separable Symmetric Cone Optimization

Julio López(julio.lopez***at***udp.cl)
Erik Papa Quiroz(erikpapa***at***gmailcom)

Abstract: This work is devoted to the study of a proximal decomposition algorithm for solving convex symmetric cone optimization with separable structures. The algorithm considered is based on the decomposition method proposed by Chen and Teboulle (1994), and the proximal generalized distance defined by Auslender and Teboulle (2006). Under suitable assumptions, first a class of proximal distances is constructed, therefore some examples are given. Second, it is proven that each limit point of the primal-dual sequences generated by the algorithm solves the problem. Finally, the global convergence is established.

Keywords: Euclidean Jordan algebra, symmetric cone optimization, decomposition method, proximal distance, proximal multiplier method.

Category 1: Convex and Nonsmooth Optimization

Citation:

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Entry Submitted: 09/29/2014
Entry Accepted: 09/29/2014
Entry Last Modified: 09/29/2014

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