Some best proximity point results for multivalued mappings on partial metric spaces
Mathematica Moravica, Tome 25 (2021) no. 1.
Voir la notice de l'article dans eLibrary of Mathematical Institute of the Serbian Academy of Sciences and Arts
In this paper, we introduce two new concepts of Feng-Liu type multivalued contraction mapping and cyclic Feng-Liu type multivalued contraction mapping. Then, we obtain some new best proximity point results for such mappings on partial metric spaces by considering Feng-Liu’s technique. Finally, we provide examples to show the effectiveness of our results.
@article{MM3_2021_25_1_a7, author = {Mustafa Aslantas and Doaa Riyadh Abed Al-Zuhairi}, title = {Some best proximity point results for multivalued mappings on partial metric spaces}, journal = {Mathematica Moravica}, pages = {99 - 111}, publisher = {mathdoc}, volume = {25}, number = {1}, year = {2021}, url = {https://geodesic-test.mathdoc.fr/item/MM3_2021_25_1_a7/} }
TY - JOUR AU - Mustafa Aslantas AU - Doaa Riyadh Abed Al-Zuhairi TI - Some best proximity point results for multivalued mappings on partial metric spaces JO - Mathematica Moravica PY - 2021 SP - 99 EP - 111 VL - 25 IS - 1 PB - mathdoc UR - https://geodesic-test.mathdoc.fr/item/MM3_2021_25_1_a7/ ID - MM3_2021_25_1_a7 ER -
%0 Journal Article %A Mustafa Aslantas %A Doaa Riyadh Abed Al-Zuhairi %T Some best proximity point results for multivalued mappings on partial metric spaces %J Mathematica Moravica %D 2021 %P 99 - 111 %V 25 %N 1 %I mathdoc %U https://geodesic-test.mathdoc.fr/item/MM3_2021_25_1_a7/ %F MM3_2021_25_1_a7
Mustafa Aslantas; Doaa Riyadh Abed Al-Zuhairi. Some best proximity point results for multivalued mappings on partial metric spaces. Mathematica Moravica, Tome 25 (2021) no. 1. https://geodesic-test.mathdoc.fr/item/MM3_2021_25_1_a7/