Strict Constraint Qualifications and Sequential Optimality Conditions for Constrained Optimization

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,...

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Veröffentlicht in:Mathematics of operations research 2018-08, Vol.43 (3), p.693-717
Hauptverfasser: Andreani, Roberto, Martínez, José Mario, Ramos, Alberto, Silva, Paulo J. S.
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Ramos, Alberto
Silva, Paulo J. S.
description 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.
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subjects algorithmic convergence
Algorithms
constraint qualifications
Constraints
Kuhn-Tucker method
nonlinear programming
Operations research
Optimization
Optimization algorithms
Qualifications
Studies
title Strict Constraint Qualifications and Sequential Optimality Conditions for Constrained Optimization
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