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Chance constrained problems: penalty reformulation and performance of sample approximation technique

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    SYSNO ASEP0376766
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleChance constrained problems: penalty reformulation and performance of sample approximation technique
    Author(s) Branda, Martin (UTIA-B) RID, ORCID
    Number of authors1
    Source TitleKybernetika. - : Ústav teorie informace a automatizace AV ČR, v. v. i. - ISSN 0023-5954
    Roč. 48, č. 1 (2012), s. 105-122
    Number of pages18 s.
    Languageeng - English
    CountryCZ - Czech Republic
    Keywordschance constrained problems ; penalty functions ; asymptotic equivalence ; sample approximation technique ; investment problem
    Subject RIVBB - Applied Statistics, Operational Research
    R&D ProjectsGBP402/12/G097 GA ČR - Czech Science Foundation (CSF)
    CEZAV0Z10750506 - UTIA-B (2005-2011)
    UT WOS000301269800006
    AnnotationWe explore reformulation of nonlinear stochastic programs with several joint chance constraints by stochastic programs with suitably chosen penalty-type objectives. We show that the two problems are asymptotically equivalent. Simpler cases with one chance constraint and particular penalty functions were studied in [6,11]. The obtained problems with penalties and with a fixed set of feasible solutions are simpler to solve and analyze then the chance constrained programs. We discuss solving both problems using Monte-Carlo simulation techniques for the cases when the set of feasible solution is finite or infinite bounded. The approach is applied to a financial optimization problem with Value at Risk constraint, transaction costs and integer allocations. We compare the ability to generate a feasible solution of the original chance constrained problem using the sample approximations of the chance constraints directly or via sample approximation of the penalty function objective.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2013
Number of the records: 1  

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