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Slater Condition for Tangent Derivatives

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  • Xi Yin Zheng

    (Department of Mathematics, Yunnan University, Kunming 650091, People’s Republic of China)

Abstract

Noting that the existing Slater condition, as a fundamental constraint qualification in optimization, is only applicable in the convex setting, we introduce and study the Slater condition for the Bouligand and Clarke tangent derivatives of a general vector-valued function F with respect to a closed convex cone K . Without any assumption, it is proved that the Slater condition for the Clarke (respectively, Bouligand) tangent derivative with respect to K is always stable when the objective function F undergoes small Lipschitz (calm) perturbations. Based on this, we prove that if the Clarke (Bouligand) tangent derivative of F satisfies the Slater condition (with respect to K ) then the conic inequality determined by F has a stable metric subregularity when F undergoes small Lipschitz (calm regular) perturbations. In the composite-convexity case, the converse implication is also proved to be true. Moreover, under the Slater condition for the tangent derivative of F , it is proved that the normal cone to the sublevel set of F can be formulated by the subdifferential of F , which improves the corresponding results in either the smooth or convex case. As applications, without any qualification assumption, we improve and generalize formulas for the normal cone to a convex sublevel set by Cabot and Thibault [(2014), Sequential formulae for the normal cone to sublevel sets. Transactions of the American Mathematical Society 366(12):6591–6628]. With the help of these formulas, some new Karush–Kuhn–Tucker optimality conditions are established.

Suggested Citation

  • Xi Yin Zheng, 2022. "Slater Condition for Tangent Derivatives," Mathematics of Operations Research, INFORMS, vol. 47(4), pages 3282-3303, November.
  • Handle: RePEc:inm:ormoor:v:47:y:2022:i:4:p:3282-3303
    DOI: 10.1287/moor.2021.1246
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    References listed on IDEAS

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    3. Hui Hu, 2005. "Characterizations of the Strong Basic Constraint Qualifications," Mathematics of Operations Research, INFORMS, vol. 30(4), pages 956-965, November.
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