On nonsmooth and discontinuous problems of stochastic systems optimization

Ermoliev YM & Norkin VI (1997). On nonsmooth and discontinuous problems of stochastic systems optimization. European Journal of Operational Research 101 (2): 230-244. DOI:10.1016/S0377-2217(96)00395-5.

Full text not available from this repository.

Abstract

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, and pollution control. The results of Ermoliev et al. are extended to the case of stochastic systems and general constraints. It is shown that the concept of stochastic mollifier gradient leads to easily implementable computational procedures for systems with Lipschitz and discontinuous objective functions. New optimality conditions are formulated for designing stochastic search procedures for constrained optimization of discontinuous systems.

Item Type: Article
Uncontrolled Keywords: Stochastic approximation; Deterministic counterpart; Discontinuity; Theory of distributions; Subgradients; Stochastic quasi-gradients; Networks; Risk; Mollifiers
Research Programs: Risk, Modeling, Policy (RMP)
Bibliographic Reference: European Journal of Operational Research; 101:230-244 [1997]
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:08
Last Modified: 29 Sep 2016 11:21
URI: http://pure.iiasa.ac.at/5051

Actions (login required)

View Item View Item

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313