Global Optimization and Common Best Proximity Points for Some Multivalued Contractive Pairs of Mappings

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 07 Sep 2020 English Publisher:MDPI AGJournal:Axioms, volume 9, page 102 (eissn: 2075-1680,

Copyright policy )

Authors: Pradip Debnath; Hari Mohan Srivastava;

doi: 10.3390/axioms9030102

Global Optimization and Common Best Proximity Points for Some Multivalued Contractive Pairs of Mappings

- Summary
- Subjects
- Metrics

Abstract

In this paper, we study a problem of global optimization using common best proximity point of a pair of multivalued mappings. First, we introduce a multivalued Banach-type contractive pair of mappings and establish criteria for the existence of their common best proximity point. Next, we put forward the concept of multivalued Kannan-type contractive pair and also the concept of weak Δ-property to determine the existence of common best proximity point for such a pair of maps.

Related Organizations

University of Victoria
Canada
China Medical University
Taiwan
Assam University
India
China Medical University Hospital
Taiwan
Azerbaijan University
Azerbaijan

Keywords

common best proximity point, fixed point, complete metric space, QA1-939, contraction map, multivalued map, optimization, Mathematics

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	19
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%