Relaxed constant positive linear dependence constraint qualification for disjunctive programs
Mengwei Xu, Jane J. Ye

TL;DR
This paper introduces a relaxed constraint qualification called RCPLD for disjunctive systems, including special cases like MPEC, MPVC, and MPSC, to establish local error bounds under various regularity conditions.
Contribution
It proposes a weaker RCPLD condition for disjunctive systems and extends it to piecewise RCPLD, ensuring error bounds for complex mathematical programs.
Findings
RCPLD is weaker than previous qualifications for disjunctive systems.
Piecewise RCPLD guarantees local error bounds when certain regularity conditions hold.
The framework applies to MPEC, MPVC, and MPSC, unifying constraint qualification approaches.
Abstract
The disjunctive system is a system involving a disjunctive set which is the union of finitely many polyhedral convex sets. In this paper, we introduce a notion of the relaxed constant positive linear dependence constraint qualification (RCPLD) for the disjunctive system. For a disjunctive system, our notion is weaker than the one we introduced for a more general system recently (J. Glob. Optim. 2020) and is still a constraint qualification. To obtain the local error bound for the disjunctive system, we introduce the piecewise RCPLD under which the error bound property holds if all inequality constraint functions are subdifferentially regular and the rest of the constraint functions are smooth. We then specialize our results to the ortho-disjunctive program, which includes the mathematical program with equilibrium constraints (MPEC), the mathematical program with vanishing constraints…
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Taxonomy
TopicsOptimization and Variational Analysis · Optimization and Mathematical Programming · Aortic aneurysm repair treatments
