Thin and heavy tails in stochastic programming

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00447994" target="_blank" >RIV/67985556:_____/15:00447994 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.14736/kyb-2015-3-0433" target="_blank" >http://dx.doi.org/10.14736/kyb-2015-3-0433</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14736/kyb-2015-3-0433" target="_blank" >10.14736/kyb-2015-3-0433</a>

Result language

angličtina

Original language name

Thin and heavy tails in stochastic programming

Original language description

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 probab

Czech name

—

Czech description

—

Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

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Project

<a href="/en/project/GA13-14445S" target="_blank" >GA13-14445S: New Trends in Stochastic Economic Models under Uncertainty</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Kybernetika

ISSN

0023-5954

e-ISSN

—

Volume of the periodical

51

Issue of the periodical within the volume

3

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

24

Pages from-to

433-456

UT code for WoS article

000361266300005

EID of the result in the Scopus database

2-s2.0-84940041736