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Chance constrained problems: penalty reformulation and performance of sample approximation technique
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SYSNO ASEP 0376766 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Chance constrained problems: penalty reformulation and performance of sample approximation technique Author(s) Branda, Martin (UTIA-B) RID, ORCID Number of authors 1 Source Title Kybernetika. - : Ústav teorie informace a automatizace AV ČR, v. v. i. - ISSN 0023-5954
Roč. 48, č. 1 (2012), s. 105-122Number of pages 18 s. Language eng - English Country CZ - Czech Republic Keywords chance constrained problems ; penalty functions ; asymptotic equivalence ; sample approximation technique ; investment problem Subject RIV BB - Applied Statistics, Operational Research R&D Projects GBP402/12/G097 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) UT WOS 000301269800006 Annotation We 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. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2013
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