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On M-stationarity conditions in MPECs and the associated qualification conditions

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    SYSNO ASEP0474227
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleOn M-stationarity conditions in MPECs and the associated qualification conditions
    Author(s) Adam, Lukáš (UTIA-B)
    Henrion, R. (DE)
    Outrata, Jiří (UTIA-B) RID, ORCID
    Number of authors3
    Source TitleMathematical Programming. - : Springer - ISSN 0025-5610
    Roč. 168, 1-2 (2018), s. 229-259
    Number of pages31 s.
    Publication formPrint - P
    Languageeng - English
    CountryNL - Netherlands
    KeywordsMathematical programs with equilibrium constraints ; Optimality conditions ; Constraint qualification ; Calmness ; Perturbation mapping
    Subject RIVBA - General Mathematics
    OECD categoryPure mathematics
    R&D ProjectsGA15-00735S GA ČR - Czech Science Foundation (CSF)
    Institutional supportUTIA-B - RVO:67985556
    UT WOS000426071000010
    EID SCOPUS85017593151
    DOI10.1007/s10107-017-1146-3
    AnnotationDepending 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.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2019
Number of the records: 1  

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