Inexact Proximal Point Methods for Quasiconvex Minimization on Hadamard Manifolds

Published: 2015/03/03, Updated: 2015/03/15

Generalized Convexity/Monoticity, Global Optimization, Nonsmooth Optimization abstract subdifferential, hadamard manifolds, nonsmooth optimization, proximal point algorithm, quasiconvex function Short URL: https://optimization-online.org/?p=13306

In this paper we present two inexact proximal point algorithms to solve minimization problems for quasiconvex objective functions on Hadamard manifolds. We prove that under natural assumptions the sequence generated by the algorithms are well defined and converge to critical points of the problem. We also present an application of the method to demand theory in economy

Inexact Proximal Point Methods for Quasiconvex Minimization on Hadamard Manifolds

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