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On M-stationarity conditions in MPECs and the associated qualification conditions
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SYSNO ASEP 0474227 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title On M-stationarity conditions in MPECs and the associated qualification conditions Author(s) Adam, Lukáš (UTIA-B)
Henrion, R. (DE)
Outrata, Jiří (UTIA-B) RID, ORCIDNumber of authors 3 Source Title Mathematical Programming. - : Springer - ISSN 0025-5610
Roč. 168, 1-2 (2018), s. 229-259Number of pages 31 s. Publication form Print - P Language eng - English Country NL - Netherlands Keywords Mathematical programs with equilibrium constraints ; Optimality conditions ; Constraint qualification ; Calmness ; Perturbation mapping Subject RIV BA - General Mathematics OECD category Pure mathematics R&D Projects GA15-00735S GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 UT WOS 000426071000010 EID SCOPUS 85017593151 DOI 10.1007/s10107-017-1146-3 Annotation Depending on whether a mathematical program with equilibrium constraints (MPEC) is considered in its original or its enhanced (via KKT conditions) form, the assumed qualification conditions as well as the derived necessary optimality conditions may differ significantly. In this paper, we study this issue when imposing one of the weakest possible qualification conditions, namely the calmness of the perturbation mapping associated with the respective generalized equations in both forms of the MPEC. It is well known that the calmness property allows one to derive the so-called M-stationarity conditions. The restrictiveness of assumptions and the strength of conclusions in the two forms of theMPECis also strongly related to the qualification conditions on the “lower level”. For instance, even under the linear independence constraint qualification (LICQ) for a lower level feasible set described by C^1 functions, the calmness properties of the original and the enhanced perturbation mapping are drastically different. When passing to C^{1,1} data, this difference still remains true under the weaker Mangasarian–Fromovitz constraint qualification, whereas under LICQ both the calmness assumption and the derived optimality conditions are fully equivalent for the original and the enhanced form of the MPEC. After clarifying these relations, we provide a compilation of practically relevant consequences of our analysis in the derivation of necessary optimality conditions. The obtained results are finally applied to MPECs with structured equilibria. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2019
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