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Closeness centrality reconstruction of tree graphs

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Abstract

This paper deals with a problem which belongs to the general question: how to reconstruct a graph from limited amount of information. As given information, we use the closeness centrality, which assigns a non-negative number to each node of the graph in question: the reciprocal of the sum of the length of the shortest paths between the node and all other nodes in the graph. Here we consider the case when the original graph is a tree and it is also known which nodes are the leaves. Based on some theoretical results, three algorithms are proposed. The first one aims at finding a non-exact solution \(G_P\) in short time; the second one is a metaheuristic with some variants, they are intended to give further improvement on \(G_P\); and the third one is designed for giving accurate results. Detailed explanations of these algorithms are given, together with numerical experiments to demonstrate their efficiency.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Notes

  1. The ’outer’ nodes are the leaves, ’inner’ nodes are the non-leaves.

  2. This is a change-making-like problem (Wright 1975).

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Acknowledgements

We thank our reviewers for their critical comments and valuable suggestions that highlighted important details and helped us in improving our paper. The research leading to these results has received funding from the national project TKP2021-NVA-09. Project no. TKP2021-NVA-09 has been implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development and Innovation Fund, financed under the TKP2021-NVA funding scheme. It was also supported by the grant SNN-135643 of the National Research, Development and Innovation Office, Hungary.

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Correspondence to Tamás Vinkó.

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Homolya, V., Vinkó, T. Closeness centrality reconstruction of tree graphs. Cent Eur J Oper Res 32, 1061–1088 (2024). https://doi.org/10.1007/s10100-023-00900-1

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