Hybrid Algorithm of Fixed Point for Weak Relatively NonexpansiveMultivalued Mappings and Applications
Author(s) -
Jingling Zhang,
Yongfu Su,
Qingqing Cheng
Publication year - 2012
Publication title -
abstract and applied analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.228
H-Index - 56
eISSN - 1687-0409
pISSN - 1085-3375
DOI - 10.1155/2012/479438
Subject(s) - mathematics , monotone polygon , fixed point , resolvent , convergence (economics) , banach space , weak convergence , projection (relational algebra) , monotonic function , operator (biology) , pure mathematics , discrete mathematics , algorithm , mathematical analysis , computer science , geometry , biochemistry , chemistry , computer security , repressor , transcription factor , economics , asset (computer security) , gene , economic growth
The purpose of this paper is to present the notion of weak relativelynonexpansive multi-valued mapping and to prove the strong convergence theorems of fixed point for weak relatively nonexpansive multivalued mappings in Banach spaces. The weak relatively nonexpansive multivalued mappings are more generalized than relatively nonexpansive multivalued mappings. In this paper, an example will be given which is a weak relatively nonexpansive multivalued mapping but not a relatively nonexpansive multivalued mapping. In order to get the strong convergence theorems for weak relatively nonexpansive multivalued mappings, a new monotone hybrid iteration algorithm with generalized (metric) projection is presented and is used to approximate the fixed point of weak relatively nonexpansive multivalued mappings. In this paper, the notion of multivalued resolvent of maximal monotone operator has been also presented which is a weak relatively nonexpansive multivalued mapping and can be used to find the zero point of maximal monotone operator
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