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Approximative solutions of stochastic optimization problem
- 1.0348335 - ÚTIA 2011 RIV CZ eng J - Článek v odborném periodiku
Lachout, Petr
Approximative solutions of stochastic optimization problem.
Kybernetika. Roč. 46, č. 3 (2010), s. 513-523. ISSN 0023-5954
Grant CEP: GA ČR GA201/08/0539
Výzkumný záměr: CEZ:AV0Z10750506
Klíčová slova: Stochastic optimization problem * sensitivity * approximative solution
Kód oboru RIV: BA - Obecná matematika
Impakt faktor: 0.461, rok: 2010
http://library.utia.cas.cz/separaty/2010/SI/lachout-approximative solutions of stochastic optimization problem.pdf
The aim of this paper is to present some ideas how to relax the notion of the optimal solution of the stochastic optimization problem. In the deterministic case, $/varepsilon $-minimal solutions and level-minimal solutions are considered as desired relaxations. We call them approximative solutions and we introduce some possibilities how to combine them with randomness. Relations among random versions of approximative solutions and their consistency are presented in this paper. No measurability is assumed, therefore, treatment convenient for nonmeasurable objects is employed.
Trvalý link: http://hdl.handle.net/11104/0188892
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