Second order optimality conditions for minimization on a general set. Part 1: Applications to mathematical programming

This paper is devoted to second-order optimality conditions for minimization of a C2 function f on a general set K in a Banach space X. We consider both necessary and sufficient conditions of the second-order which differ by the strengthening of inequalities in their formulations. The conditions use...

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Published inJournal of mathematical analysis and applications Vol. 529; no. 2; p. 127384
Main Authors Frankowska, Hélène, Osmolovskii, Nikolai P.
Format Journal Article
LanguageEnglish
Published Elsevier Inc 15.01.2024
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Abstract This paper is devoted to second-order optimality conditions for minimization of a C2 function f on a general set K in a Banach space X. We consider both necessary and sufficient conditions of the second-order which differ by the strengthening of inequalities in their formulations. The conditions use first and second order approximations (first and second-order tangents) of the set K. The no gap sufficient conditions need additional assumptions in comparison with necessary conditions. We show that these assumptions hold true in the case when the set K is an intersection of a finite number of sets described by smooth inequalities and equalities, like in problems of the mathematical programming. Moreover, we illustrate the new conditions by deducing some mathematical programming results. In this sense the paper is partly a survey. One non-trivial illustrative example in an infinite dimensional space concerns the case when K can not be represented as an intersection described above. The novelty of our approach is due, on one hand, to the arbitrariness of the set K, and on the other hand, to quite straightforward proofs.
AbstractList This paper is devoted to second-order optimality conditions for minimization of a C2 function f on a general set K in a Banach space X. We consider both necessary and sufficient conditions of the second-order which differ by the strengthening of inequalities in their formulations. The conditions use first and second order approximations (first and second-order tangents) of the set K. The no gap sufficient conditions need additional assumptions in comparison with necessary conditions. We show that these assumptions hold true in the case when the set K is an intersection of a finite number of sets described by smooth inequalities and equalities, like in problems of the mathematical programming. Moreover, we illustrate the new conditions by deducing some mathematical programming results. In this sense the paper is partly a survey. One non-trivial illustrative example in an infinite dimensional space concerns the case when K can not be represented as an intersection described above. The novelty of our approach is due, on one hand, to the arbitrariness of the set K, and on the other hand, to quite straightforward proofs.
ArticleNumber 127384
Author Osmolovskii, Nikolai P.
Frankowska, Hélène
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  organization: CNRS, IMJ-PRG, Sorbonne Université, Case 247, 4 Place Jussieu, 75252 Paris, France
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  givenname: Nikolai P.
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  organization: Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warszawa, Poland
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Cites_doi 10.1007/s00245-017-9461-x
10.1007/BFb0120982
10.1137/S1052623496306760
10.6028/jres.049.027
10.1007/BF01585095
10.1070/RM1978v033n06ABEH003885
10.1007/BF01445166
10.1287/moor.2021.1211
10.1137/110828320
10.1137/17M1160604
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Keywords Local minimum
Equality and inequality constraints
Separation theorem
Second order optimality conditions
Lagrange function
First and second order tangents
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Bonnans (10.1016/j.jmaa.2023.127384_br0030) 1999; 9
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Snippet This paper is devoted to second-order optimality conditions for minimization of a C2 function f on a general set K in a Banach space X. We consider both...
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StartPage 127384
SubjectTerms Equality and inequality constraints
First and second order tangents
Lagrange function
Local minimum
Second order optimality conditions
Separation theorem
Title Second order optimality conditions for minimization on a general set. Part 1: Applications to mathematical programming
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