Sample approximation technique for mixed-integer stochastic programming problems with expected value constraints

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10135324" target="_blank" >RIV/00216208:11320/14:10135324 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s11590-013-0642-5" target="_blank" >http://dx.doi.org/10.1007/s11590-013-0642-5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11590-013-0642-5" target="_blank" >10.1007/s11590-013-0642-5</a>

Result language
angličtina
Original language name
Sample approximation technique for mixed-integer stochastic programming problems with expected value constraints
Original language description
The paper deals with the theory of sample approximation techniques applied to stochastic programming problems with expected value constraints. We extend the results on the rates of convergence to the problems with a mixed-integer bounded set of feasiblesolutions and several expected value constraints. Moreover, we enable non-iid sampling and consider Hölder-calmness of the constraints. We derive estimates on the sample size necessary to get a feasible solution or a lower bound on the optimal value of the original problem using the sample approximation. We present an application of the estimates to an investment problem with the Conditional Value at Risk constraints, integer allocations and transaction costs.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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