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Solving joint chance constrained problems using regularization and Benders’ decomposition
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SYSNO ASEP 0501589 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Solving joint chance constrained problems using regularization and Benders’ decomposition Author(s) Adam, Lukáš (UTIA-B)
Branda, Martin (UTIA-B) RID, ORCID
Heitsch, H. (DE)
Henrion, R. (DE)Number of authors 4 Source Title Annals of Operations Research. - : Springer - ISSN 0254-5330
Roč. 292, č. 2 (2020), s. 683-709Number of pages 27 s. Publication form Print - P Language eng - English Country US - United States Keywords Stochastic programming ; Chance constrained programming ; Optimality conditions ; Regularization ; Benders' decomposition ; Gas networks Subject RIV BA - General Mathematics OECD category Pure mathematics R&D Projects GA18-04145S GA ČR - Czech Science Foundation (CSF) Method of publishing Limited access Institutional support UTIA-B - RVO:67985556 UT WOS 000563054500006 EID SCOPUS 85056150669 DOI 10.1007/s10479-018-3091-9 Annotation We consider stochastic programs with joint chance constraints with discrete random distribution. We reformulate the problem by adding auxiliary variables. Since the resulting problem has a non-regular feasible set, we regularize it by increasing the feasible set. We solve the regularized problem by iteratively solving a master problem while adding Benders’ cuts from a slave problem. Since the number of variables of the slave problem equals to the number of scenarios, we express its solution in a closed form. We show convergence properties of the solutions. On a gas network design problem, we perform a numerical study by increasing the number of scenarios and compare our solution with a solution obtained by solving the same problem with the continuous distribution. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2021 Electronic address https://link.springer.com/article/10.1007/s10479-018-3091-9
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