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Trade-Off of Networks on Weighted Space Analyzed via a Method Mimicking Human Walking Track Superposition

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Bioinspired Optimization Methods and Their Applications (BIOMA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13627))

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Abstract

This study proposes a method for constructing networks with a small total weighted length and total detour rate by mimicking human walking track superposition. The present study aims to contribute to the scarce literature on multiple objectives, the total weighted length and the total detour rate, by allowing branching vertices on weighted space. The weight on space represents the spatial difference in the implementation cost, such as buildings, terrains, and land price. In modern society, we need to design a new transportation network while considering these constraints so that the network has a low total weighted length that enables a low implementation cost and a low total detour rate that leads to high efficiency. This study contributes to this requirement. The proposed method outputs solutions with various combinations of the total weighted length and the total detour rate. It approximates the Pareto frontier by connecting inherent non-dominated solutions. This approximation enables the analysis of the relationship between the weighted space and the limit of effective networks the space can generate quantitatively. Several experiments are carried out, and the result infers that the area with a huge weight significantly affects the trade-off relationship between the total weighted length and the total detour rate. Quantitatively revealing the trade-off relationship between the total weighted length and the total detour rate is helpful in managerial situations under certain constraints, including the budget, needed operational performance, and so on.

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Acknowledgements

We would like to thank Editage (www.editage.com) for English language editing.

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Authors and Affiliations

  1. Kajima Corporation, 3-1, Motoakasaka 1-chome, Minato-ku, Tokyo, Japan

    Shota Tabata

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  1. Shota Tabata
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Correspondence to Shota Tabata .

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Editors and Affiliations

  1. University of Maribor, Maribor, Slovenia

    Marjan Mernik

  2. Jožef Stefan Institute, Ljubljana, Slovenia

    Tome Eftimov

  3. University of Maribor, Maribor, Slovenia

    Matej Črepinšek

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Tabata, S. (2022). Trade-Off of Networks on Weighted Space Analyzed via a Method Mimicking Human Walking Track Superposition. In: Mernik, M., Eftimov, T., Črepinšek, M. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2022. Lecture Notes in Computer Science, vol 13627. Springer, Cham. https://doi.org/10.1007/978-3-031-21094-5_18

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  • DOI: https://doi.org/10.1007/978-3-031-21094-5_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21093-8

  • Online ISBN: 978-3-031-21094-5

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