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A heuristic method for solving the Steiner tree problem in graphs using network centralities.
Fujita, Misa; Shimada, Yutaka; Kimura, Takayuki; Ikeguchi, Tohru.
Afiliación
  • Fujita M; Department of Electrical and Electronic Engineering, School of Engineering, Chukyo University, Nagoya-shi, Aichi, Japan.
  • Shimada Y; Department of Management Science, Graduate School of Engineering, Tokyo University of Science, Katsushika-ku, Tokyo, Japan.
  • Kimura T; Graduate School of Science and Engineering, Saitama University, Sakura-ku, Saitama, Japan.
  • Ikeguchi T; Department of Electrical, Electronics and Communication Engineering, Faculty of Fundamental Engineering, Nippon Institute of Technology, Miyashiro-cho, Minami-saitama-gun, Saitama, Japan.
PLoS One ; 19(6): e0303764, 2024.
Article en En | MEDLINE | ID: mdl-38843249
ABSTRACT
We propose a heuristic method of using network centralities for constructing small-weight Steiner trees in this paper. The Steiner tree problem in graphs is one of the practical NP-hard combinatorial optimization problems. Given a graph and a set of vertices called terminals in the graph, the objective of the Steiner tree problem in graphs is to find a minimum weight Steiner tree that is a tree containing all the terminals. Conventional construction methods make a Steiner tree based on the shortest paths between terminals. If these shortest paths are overlapped as much as possible, we can obtain a small-weight Steiner tree. Therefore, we proposed to use network centralities to distinguish which edges should be included to make a small-weight Steiner tree. Experimental results revealed that using the vertex or the edge betweenness centralities contributes to making small-weight Steiner trees.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Heurística Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: Japón

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Heurística Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2024 Tipo del documento: Article País de afiliación: Japón