Decomposition via Alternating Linearization

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/4090 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/4090 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/4090 archive 351 disk0/00/00/45/41 2016-01-15 02:06:11 2021-08-27 17:15:19 2016-01-15 02:06:11 monograph show 2 Kiwiel K. Rosa C.H. 1545 Ruszczynski A. 1475 Decomposition via Alternating Linearization pub iis_met iis_sys prog_opt A new approximate proximal point method for minimizing the sum of two convex functions is introduced. It replaces the original problem by a sequence of regularized subproblems in which the functions are alternately represented by linear models. The method updates the linear models and the prox center, as well as the prox coefficient. It is monotone in terms of the objective values and converges to a solution of the problem, if any. A dual version of the method is derived and analyzed. Applications of the methods to multistage stochastic programming problems are discussed and preliminary numerical experience presented. 1995-06 published WP-95-051 WP-95-051 10 1541 1544 public working_paper IIASA, Laxenburg, Austria 25 FALSE info:eu-repo/semantics/book