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Degree Partition Number of Some Derived Graphs.

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Title: Degree Partition Number of Some Derived Graphs.
Authors: Malathi, N.1 rmnmalathi96@gmail.com, Bhuvaneshwari, M.2 bhuvanaresearch2020@gmail.com, Avadayappan, Selvam3 selvam_avadayappan@yahoo.co.in
Source: IAENG International Journal of Applied Mathematics. Jun2025, Vol. 55 Issue 6, p1865-1872. 8p.
Subjects: Individual needs, Mathematicians
Abstract: In many places, there may emerge a situation in which a certain group of individuals or components need to be partitioned into many groups in order to meet certain requirements. To investigate the characteristics and nature of a network, our mathematicians create a variety of partitioning techniques. Usage of graph theoretical method simplifies the partitioning procedure. On the vertex set of graph G, we define a partition πκ consisting of k partition classes. πκ is said to be a similar degree partition of G if the absolute difference of the sum of the degrees of all vertices between any two partition classes is at most 1. The largest value k across all the similar degree partition of the graph G is defined to be the degree partition number of G and is denoted by ψD(G). This partition suits the need for partitioning any resource into groups of almost equal strength. In this paper we have established some interesting facts and theorems regarding the degree partition number of some derived graphs. [ABSTRACT FROM AUTHOR]
Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Degree Partition Number of Some Derived Graphs.
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  Data: <searchLink fieldCode="AR" term="%22Malathi%2C+N%2E%22">Malathi, N.</searchLink><relatesTo>1</relatesTo><i> rmnmalathi96@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Bhuvaneshwari%2C+M%2E%22">Bhuvaneshwari, M.</searchLink><relatesTo>2</relatesTo><i> bhuvanaresearch2020@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Avadayappan%2C+Selvam%22">Avadayappan, Selvam</searchLink><relatesTo>3</relatesTo><i> selvam_avadayappan@yahoo.co.in</i>
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  Data: <searchLink fieldCode="JN" term="%22IAENG+International+Journal+of+Applied+Mathematics%22">IAENG International Journal of Applied Mathematics</searchLink>. Jun2025, Vol. 55 Issue 6, p1865-1872. 8p.
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  Data: In many places, there may emerge a situation in which a certain group of individuals or components need to be partitioned into many groups in order to meet certain requirements. To investigate the characteristics and nature of a network, our mathematicians create a variety of partitioning techniques. Usage of graph theoretical method simplifies the partitioning procedure. On the vertex set of graph G, we define a partition πκ consisting of k partition classes. πκ is said to be a similar degree partition of G if the absolute difference of the sum of the degrees of all vertices between any two partition classes is at most 1. The largest value k across all the similar degree partition of the graph G is defined to be the degree partition number of G and is denoted by ψD(G). This partition suits the need for partitioning any resource into groups of almost equal strength. In this paper we have established some interesting facts and theorems regarding the degree partition number of some derived graphs. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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              Text: Jun2025
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