Generalized Proximal Distances for Bilevel Equilibrium Problems
Author(s) -
G. C. Bento,
J. X. Cruz Neto,
J. O. Lopes,
P. A. Soares,
Antoine Soubeyran
Publication year - 2016
Publication title -
siam journal on optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.066
H-Index - 136
eISSN - 1095-7189
pISSN - 1052-6234
DOI - 10.1137/140975589
Subject(s) - bilevel optimization , mathematical optimization , convergence (economics) , monotone polygon , class (philosophy) , sequence (biology) , stability (learning theory) , point (geometry) , equilibrium point , computer science , optimization problem , mathematics , artificial intelligence , mathematical analysis , geometry , machine learning , biology , economics , genetics , differential equation , economic growth
We consider a bilevel problem involving two monotone equilibrium bifunctions and we show that this problem can be solved by a proximal point method with generalized proximal distances. We propose a framework for the convergence analysis of the sequence generated by the algorithm. This class of problems is very interesting because it covers mathematical programs and optimization problems under equilibrium constraints. As an application, we consider the problem of the stability and change dynamics of a leader-follower relationship in a hierarchical organization.
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