On Nonsmooth Problems of Stochastic Systems Optimization

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/4048 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/4048 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/4048 archive 351 disk0/00/00/45/00 2016-01-15 02:05:58 2021-08-27 17:15:14 2016-01-15 02:05:58 monograph show 2 Ermoliev Y.M. 1445 Norkin V.I. AL1055 On Nonsmooth Problems of Stochastic Systems Optimization pub iis_met iis_rsk prog_rpc A class of stochastic optimization problems is analyzed that cannot be solved by deterministic and standard stochastic approximation methods. We consider risk control problems, optimization of stochastic networks and discrete event systems, screening irreversible changes, pollution control. The results of Ermoliev, Norkin, Wets [11] are extended to the case of problems involving random variables and general constraints. It is shown that the concept of mollifier subgradient leads to easily implementable computational procedures for stochastic systems with Lipschitz and discontinuous expectation functions. New optimality conditions are formulated enabling to design stochastic search procedures for constrained optimization of discontinuous systems. 1995-12 published WP-95-096 WP-95-096 10 338 2245 public working_paper IIASA, Laxenburg, Austria 40 FALSE info:eu-repo/semantics/book