bibtype J - Journal Article
ARLID 0450553
utime 20240103211213.2
mtime 20160215235959.9
SCOPUS 84941338155
WOS 000374450100005
DOI 10.1007/s10100-015-0414-7
title (primary) (eng) A remark on multiobjective stochastic optimization via strongly convex functions
specification
page_count 25 s.
media_type P
serial
ARLID cav_un_epca*0293028
ISSN 1435-246X
title Central European Journal of Operations Research
volume_id 24
volume 2 (2016)
page_num 309-333
keyword Stochasticmultiobjective optimization problem
keyword Efficient solution
keyword Wasserstein metric and L_1 norm
keyword Stability and empirical estimates
author (primary)
ARLID cav_un_auth*0101122
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
full_dept Department of Econometrics
share 100
name1 Kaňková
name2 Vlasta
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2015/E/kankova-0450553.pdf
cas_special
project
ARLID cav_un_auth*0292652
project_id GA13-14445S
agency GA ČR
abstract (eng) Many economic and financial applications lead (from the mathematical point of view) to deterministic optimization problems depending on a probability measure. These problems can be static (one stage), dynamic with finite (multistage) or infinite horizon, single objective or multiobjective. We focus on one-stage case in multiobjective setting. Evidently, well known results from the deterministic optimization theory can be employed in the case when the "underlying" probability measure is completely known. The assumption of a complete knowledge of the probability measure is fulfilled very seldom. Consequently, we have mostly to analyze the mathematical models on the data base to obtain a stochastic estimate of the corresponding "theoretical" characteristics. However, the investigation of these estimates has been done mostly in one-objective case. In this paper we focus on the investigation of the relationship between "characteristics" obtained on the base of complete knowledge of the probability measure and estimates obtained on the (above mentioned) data base, mostly in the multiobjective case.
RIV BB
reportyear 2017
num_of_auth 1
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0252048
confidential S
mrcbC86 3+4 Article Operations Research Management Science
mrcbT16-e OPERATIONSRESEARCHMANAGEMENTSCIENCE
mrcbT16-j 0.305
mrcbT16-s 0.531
mrcbT16-4 Q3
mrcbT16-B 7.294
mrcbT16-D Q4
mrcbT16-E Q3
arlyear 2016
mrcbU14 84941338155 SCOPUS
mrcbU34 000374450100005 WOS
mrcbU63 cav_un_epca*0293028 Central European Journal of Operations Research 1435-246X 1613-9178 Roč. 24 č. 2 2016 309 333