Approximative solutions of stochastic optimization problem
1.
SYSNO ASEP
0348335
Druh ASEP
J - Článek v odborném periodiku
Zařazení RIV
J - Článek v odborném periodiku
Poddruh J
Článek ve WOS
Název
Approximative solutions of stochastic optimization problem
Tvůrce(i)
Lachout, Petr (UTIA-B)
Zdroj.dok.
Kybernetika. - : Ústav teorie informace a automatizace AV ČR, v. v. i.
- ISSN 0023-5954
Roč. 46, č. 3 (2010), s. 513-523
Poč.str.
11 s.
Jazyk dok.
eng - angličtina
Země vyd.
CZ - Česká republika
Klíč. slova
Stochastic optimization problem ; sensitivity ; approximative solution
Vědní obor RIV
BA - Obecná matematika
CEP
GA201/08/0539 GA ČR - Grantová agentura ČR
CEZ
AV0Z10750506 - UTIA-B (2005-2011)
UT WOS
000280425000015
Anotace
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.
