Optimizing Wiener and Randić Indices of Graphs. (26th September 2020)
- Record Type:
- Journal Article
- Title:
- Optimizing Wiener and Randić Indices of Graphs. (26th September 2020)
- Main Title:
- Optimizing Wiener and Randić Indices of Graphs
- Authors:
- Mahasinghe, A. C.
Erandi, K. K. W. H.
Perera, S. S. N. - Other Names:
- Jones Dylan F. Academic Editor.
- Abstract:
- Abstract : Wiener and Randić indices have long been studied in chemical graph theory as connection strength measures of graphs. Later, these indices were used in different fields such as network analysis. We consider two optimization problems related to these indices, with potential applications to network theory, in particular to epidemiological networks. Given a connected graph and a fixed total edge weight, we investigate how individual weights must be assigned to edges, minimizing the connection strength of the graph. In order to measure the connection strength, we use the weighted Wiener index and a modified version of the ordinary Randić index. Wiener index optimization is linear, while Randić index optimization turns out to be both nonlinear and nonconvex. Hence, we adopt the technique of separable programming to generate solutions. We present our experimental results by applying relevant algorithms to several graphs.
- Is Part Of:
- Advances in operations research. Volume 2020(2020)
- Journal:
- Advances in operations research
- Issue:
- Volume 2020(2020)
- Issue Display:
- Volume 2020, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 2020
- Issue:
- 2020
- Issue Sort Value:
- 2020-2020-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09-26
- Subjects:
- Operations research -- Periodicals
Operations research
Periodicals
003 - Journal URLs:
- https://www.hindawi.com/journals/aor/ ↗
http://bibpurl.oclc.org/web/44187 ↗ - DOI:
- 10.1155/2020/3139867 ↗
- Languages:
- English
- ISSNs:
- 1687-9147
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 14376.xml