arXiv Analytics

Sign in

arXiv:0710.1463 [math.OC]AbstractReferencesReviewsResources

Convex minimization problems with weak constraint qualifications

Christian Léonard

Published 2007-10-08Version 1

One revisits the standard saddle-point method based on conjugate duality for solving convex minimization problems. Our aim is to reduce or remove unnecessary topological restrictions on the constraint set. Dual equalities and characterizations of the minimizers are obtained with weak or without constraint qualifications. The main idea is to work with intrinsic topologies which reflect some geometry of the objective function. The abstract results of this article are applied in other papers to the Monge-Kantorovich optimal transport problem and the minimization of entropy functionals.

Related articles: Most relevant | Search more
arXiv:math/0607604 [math.OC] (Published 2006-07-24)
Characterization of the optimal plans for the Monge-Kantorovich transport problem
arXiv:2007.14653 [math.OC] (Published 2020-07-29)
Relations between Abs-Normal NLPs and MPCCs Part 2: Weak Constraint Qualifications
arXiv:1610.01970 [math.OC] (Published 2016-10-06)
Adaptive Sequential Stochastic Optimization