bibtype K - Conference Paper (Czech conference)
ARLID 0536237
utime 20250123090608.7
mtime 20201215235959.9
WOS 000668460800038
title (primary) (eng) A Note on Stochastic Optimization Problems with Nonlinear Dependence on a Probability Measure
specification
page_count 6 s.
media_type P
serial
ARLID cav_un_epca*0536245
ISBN 978-80-7509-734-7
title Proceedings of the 38th International Conference on Mathematical Methods in Economics
page_num 247-252
publisher
place Brno
name Faculty of Business Economics, Mendel University
year 2020
editor
name1 Kapounek
name2 S.
editor
name1 Vránová
name2 H.
keyword Stochastic optimization problem
keyword Nonlinear dependence
keyword Empirical estimates
keyword Static problems
author (primary)
ARLID cav_un_auth*0101122
name1 Kaňková
name2 Vlasta
institution UTIA-B
full_dept (cz) Ekonometrie
full_dept (eng) Department of Econometrics
department (cz) E
department (eng) E
share 100
garant K
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2020/E/kankova-0536237.pdf
cas_special
project
project_id GA18-02739S
agency GA ČR
ARLID cav_un_auth*0363963
abstract (eng) Nonlinear dependence on a probability measure begins to appear (last time) in a stochastic optimization rather often. Namely, the corresponding type of problems corresponds to many situations in applications. The nonlinear dependence can appear as in the objective functions so in a constraints set. We plan to consider the case of static (one-objective) problems in which nonlinear dependence appears in the objective function with a few types of constraints sets. In details we consider constraints sets “deterministic”, depending nonlinearly on the probability measure, constraints set determined by second order stochastic dominance and the sets given by mean-risk problems. The last case means that the constraints set corresponds to solutions those guarantee an acceptable value in both criteria. To introduce corresponding assertions we employ the stability results based on the Wasserstein metric and L1 norm. Moreover, we try to deal also with the case when all results have to be obtained (estimated) on the data base.
action
ARLID cav_un_auth*0395560
name INTERNATIONAL CONFERENCE ON MATHEMATICAL METHODS IN ECONOMICS (MME 2020) /38./
dates 20200909
mrcbC20-s 20200911
place Brno
country CZ
RIV BB
FORD0 50000
FORD1 50200
FORD2 50202
reportyear 2021
num_of_auth 1
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0314174
confidential S
mrcbC90 90120
arlyear 2020
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 000668460800038 WOS
mrcbU63 cav_un_epca*0536245 Proceedings of the 38th International Conference on Mathematical Methods in Economics 978-80-7509-734-7 247 252 Brno Faculty of Business Economics, Mendel University 2020
mrcbU67 340 Kapounek S.
mrcbU67 340 Vránová H.