Inexact Proximal Point Methods for Multiobjective Quasiconvex Minimization on Hadamard Manifolds

被引：0
作者：
Erik Alex Papa Quiroz
Nancy Baygorrea Cusihuallpa
Nelson Maculan
机构：
[1] Universidad Nacional Mayor de San Marcos and Universidad Privada del Norte,
[2] Universidade Federal do Rio de Janeiro and Centro de Tecnologia Mineral-CETEM,undefined
[3] Universidade Federal do Rio de Janeiro,undefined
来源：
Journal of Optimization Theory and Applications | 2020年 / 186卷
关键词：
Proximal point methods; Quasiconvex function; Hadamard manifolds; Multiobjective optimization; Pareto optimality; 49M37; 65K05; 65K10; 90C26; 90C29;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we present two inexact scalarization proximal point methods to solve quasiconvex multiobjective minimization problems on Hadamard manifolds. Under standard assumptions on the problem, we prove that the two sequences generated by the algorithms converge to a Pareto critical point of the problem and, for the convex case, the sequences converge to a weak Pareto solution. Finally, we explore an application of the method to demand theory in economy, which can be dealt with using the proposed algorithm.
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页码：879 / 898
页数：19
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