Journal of the Operations Research Society of China ›› 2016, Vol. 4 ›› Issue (4): 397-.doi: 10.1007/s40305-016-0133-3
Special Issue: Continuous Optimization
• Continuous Optimization • Next Articles
Online:
Published:
Abstract:
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.
Key words: Proximal point method ·, Quasiconvex function ·, Hadamard manifolds · Nonsmooth optimization ·, Abstract subdifferential
Nancy Baygorrea· Erik Alex Papa Quiroz ·Nelson Maculan. Inexact Proximal Point Methods for Quasiconvex Minimization on Hadamard Manifolds[J]. Journal of the Operations Research Society of China, 2016, 4(4): 397-.
0 / / Recommend
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
URL: https://www.jorsc.shu.edu.cn/EN/10.1007/s40305-016-0133-3
https://www.jorsc.shu.edu.cn/EN/Y2016/V4/I4/397