Počet záznamů: 1
Thin and heavy tails in stochastic programming
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SYSNO ASEP 0447994 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Thin and heavy tails in stochastic programming Tvůrce(i) Kaňková, Vlasta (UTIA-B) RID
Houda, Michal (UTIA-B) ORCIDZdroj.dok. Kybernetika. - : Ústav teorie informace a automatizace AV ČR, v. v. i. - ISSN 0023-5954
Roč. 51, č. 3 (2015), s. 433-456Poč.str. 24 s. Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. CZ - Česká republika Klíč. slova stochastic programming problems ; stability ; Wasserstein metric ; L1 norm ; Lipschitz property ; empirical estimates ; convergence rate ; linear and nonlinear dependence ; probability and risk constraints ; stochastic dominance Vědní obor RIV BB - Aplikovaná statistika, operační výzkum CEP GA13-14445S GA ČR - Grantová agentura ČR Institucionální podpora UTIA-B - RVO:67985556 UT WOS 000361266300005 EID SCOPUS 84940041736 DOI 10.14736/kyb-2015-3-0433 Anotace Optimization problems depending on a probability measure correspond to many applications. These problems can be static (single-stage), dynamic with finite (multi-stage) or infinite horizon, single- or multi-objective. It is necessary to have complete knowledge of the underlying probability measure if we are to solve the above-mentioned problems with precision. However this assumption is very rarely fulfilled (in applications) and consequently, problems have to be solved mostly on the basis of data. Stochastic estimates of an optimal value and an optimal solution can only be obtained using this approach. Properties of these estimates have been investigated many times. In this paper we intend to study one-stage problems under unusual (corresponding to reality, however) assumptions. In particular, we try to compare the achieved results under the assumptions of thin and heavy tails in the case of problems with linear and nonlinear dependence on the probability measure, problems with probability and risk measure constraints, and the case of stochastic dominance constraints. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2016
Počet záznamů: 1