A biologically inspired network design model

Zhang, Xiaoge, Adamatzky, Andrew, Chan, Felix T. S., Deng, Yong, Yang, Hai, Yang, Xin-She ORCID logoORCID: https://orcid.org/0000-0001-8231-5556, Tsompanas, Michail-Antisthenis I., Sirakoulis, Georgios Ch. and Mahadevan, Sankaran (2015) A biologically inspired network design model. Scientific Reports, 5 . ISSN 2045-2322 [Article] (doi:10.1038/srep10794)

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Abstract

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach.

Item Type: Article
Additional Information: Article number = 10794
Keywords (uncontrolled): optimization network model metaheuristic algorithm
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 17011
Notes on copyright: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
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Depositing User: Xin-She Yang
Date Deposited: 18 Jun 2015 10:11
Last Modified: 29 Nov 2022 22:45
URI: https://eprints.mdx.ac.uk/id/eprint/17011

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