TY - JOUR
T1 - Strict constraint qualifications and sequential optimality conditions for constrained optimization
AU - Andreani, Roberto
AU - Martínez, José Mario
AU - Ramos, Alberto
AU - Silva, Paulo J.S.
N1 - Publisher Copyright:
© 2018 INFORMS.
PY - 2018/8
Y1 - 2018/8
N2 - 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.
AB - 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.
KW - Algorithmic convergence
KW - Constraint qualifications
KW - Nonlinear programming
UR - https://www.scopus.com/pages/publications/85045879639
U2 - 10.1287/moor.2017.0879
DO - 10.1287/moor.2017.0879
M3 - Article
AN - SCOPUS:85045879639
SN - 0364-765X
VL - 43
SP - 693
EP - 717
JO - Mathematics of Operations Research
JF - Mathematics of Operations Research
IS - 3
ER -