A topological network connectivity design problem based on spectral analysis

•A topological network connectivity design problem based on spectral analysis is given.•The problem is a convex program and the solution is global.•It can be converted into a semidefinite programming problem.•A new interpretation of the 2nd minimum eigenvalue as a connectivity measure is given.•A me...

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Veröffentlicht in:Transportation research. Part B: methodological 2024-11, Vol.189, p.103012, Article 103012
Hauptverfasser: Nakayama, Shoichiro, Kobayashi, Shun-ichi, Yamaguchi, Hiromichi
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Sprache:eng
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Zusammenfassung:•A topological network connectivity design problem based on spectral analysis is given.•The problem is a convex program and the solution is global.•It can be converted into a semidefinite programming problem.•A new interpretation of the 2nd minimum eigenvalue as a connectivity measure is given.•A method for identifying critical links using the Fiedler vector is provided. How to improve network connectivity and which parts of the network are vulnerable are critical issues. We begin by defining an equal distribution problem, in which supplies are distributed equally to all nodes in the network. We then derive a topological network connectivity measure from the convergence speed, which is the second minimum eigenvalue of a Laplacian network matrix. Based on the equal distribution problem, we propose a method for identifying critical links for network connectivity using the derivative of the second minimum eigenvalue. Furthermore, we develop a network design problem that maximizes topological connectivity within a budget creating strengthening network links. The problem is convex programming, and the solution is global. Furthermore, it can be converted into an identical semidefinite programming problem, which requires less computational effort. Finally, we test the developed problems on road networks in the Japanese prefectures of Ishikawa and Toyama to determine their applicability and validity.
ISSN:0191-2615
DOI:10.1016/j.trb.2024.103012