bibtype J - Journal Article
ARLID 0348335
utime 20240903170622.1
mtime 20101101235959.9
WOS 000280425000015
title (primary) (eng) Approximative solutions of stochastic optimization problem
specification
page_count 11 s.
serial
ARLID cav_un_epca*0297163
ISSN 0023-5954
title Kybernetika
volume_id 46
volume 3 (2010)
page_num 513-523
publisher
name Ústav teorie informace a automatizace AV ČR, v. v. i.
keyword Stochastic optimization problem
keyword sensitivity
keyword approximative solution
author (primary)
ARLID cav_un_auth*0101151
name1 Lachout
name2 Petr
full_dept (cz) Stochastická informatika
full_dept (eng) Department of Stochastic Informatics
department (cz) SI
department (eng) SI
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2010/SI/lachout-approximative solutions of stochastic optimization problem.pdf
cas_special
project
project_id GA201/08/0539
agency GA ČR
ARLID cav_un_auth*0239648
research CEZ:AV0Z10750506
abstract (eng) 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.
reportyear 2011
RIV BA
mrcbC52 4 O 4o 20231122134205.4
permalink http://hdl.handle.net/11104/0188892
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arlyear 2010
mrcbTft \nSoubory v repozitáři: 0348335.pdf
mrcbU34 000280425000015 WOS
mrcbU63 cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 46 č. 3 2010 513 523 Ústav teorie informace a automatizace AV ČR, v. v. i.