Proximal penalty-duality algorithms for mixed optimality conditions

被引：0
作者：
Gonzalo Alduncin
机构：
[1] Universidad Nacional Autónoma de México,Departamento de Recursos Naturales Instituto de Geofísica
来源：
Journal of Fixed Point Theory and Applications | 2017年 / 19卷
关键词：
Constrained optimal control problem; Evolution mixed variational inclusion; Optimality condition; Proximation penalty-duality algorithm; Resolvent fixed point variational characterization; Maximal monotone operator; Primary 49M29; 65K10; Secondary 49J53; 65J08;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Preconditioned proximal penalty-duality two- and three-field algorithms for mixed optimality conditions, of evolution mixed constrained optimal control problems, are considered. Fixed point existence analysis is performed for corresponding evolution mixed governing variational state systems, in reflexive Banach spaces. Further, convergence analysis of the proximal penalty-duality algorithms is established via fixed point characterizations. In both analysis, a resolvent fixed point variational strategy is applied.
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页码：1775 / 1791
页数：16
相关论文
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