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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Strict Constraint Qualifications and Sequential Optimality Conditions for Constrained Optimization

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Author(s):
Andreani, Roberto [1] ; Martinez, Jose Mario [1] ; Ramos, Alberto [2] ; Silva, Paulo J. S. [1]
Total Authors: 4
Affiliation:
[1] Univ Estadual Campinas, Inst Math Stat & Sci Comp, BR-13083970 Campinas, SP - Brazil
[2] Univ Fed Parana, Dept Math, BR-80060000 Curitiba, Parana - Brazil
Total Affiliations: 2
Document type: Journal article
Source: MATHEMATICS OF OPERATIONS RESEARCH; v. 43, n. 3, p. 693-717, AUG 2018.
Web of Science Citations: 7
Abstract

Sequential optimality conditions for constrained optimization are necessarily satisfied by local minimizers, independently of the fulfillment of constraint qualifications. These conditions support the employment of different stopping criteria for practical optimization algorithms. On the other hand, when an appropriate property on the constraints holds at a point that satisfies a sequential optimality condition, such a point also satisfies the Karush-Kuhn-Tucker conditions. Those properties will be called strict constraint qualifications in this paper. As a consequence, for each sequential optimality condition, it is natural to ask for its weakest strict associated constraint qualification. This problem has been solved in a recent paper for the Approximate Karush-Kuhn-Tucker sequential optimality condition. In the present paper, we characterize the weakest strict constraint qualifications associated with other sequential optimality conditions that are useful for defining stopping criteria of algorithms. In addition, we prove all the implications between the new strict constraint qualifications and other (classical or strict) constraint qualifications. (AU)

FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 13/05475-7 - Computational methods in optimization
Grantee:Sandra Augusta Santos
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 12/20339-0 - Penalty methods, optimality conditions, and applications
Grantee:Paulo José da Silva e Silva
Support Opportunities: Regular Research Grants