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A Novel Physarum-Based Optimization Algorithm for Shortest Path

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Advances in Swarm Intelligence (ICSI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12689))

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Abstract

As a new bio-inspired algorithm, the Physarum-based algorithm has shown great performance for solving complex computational problems. More and more researchers try to use the algorithm to solve some network optimization problems. Although the Physarum-based algorithm can figure out these problems correctly and accurately, the convergence speed of Physarum-based algorithm is relatively slow. This is mainly because many linear equations have to be solved when applying Physarum-based algorithm. Furthermore, many iterations are required using Physarum-based algorithm for network optimization problems with large number of nodes. With those observations in mind, two new methods are proposed to deal with these problems. By observing the traffic network data, there are many redundant nodes, which don’t need to be computed in practical applications. The calculation time of the algorithm is reduced by avoiding these special nodes. The convergence speed of Physarum-based algorithm can then be accelerated. Two real traffic networks and eighteen random sparse connected graphs are used to verify the performance of the proposed algorithm.

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Authors and Affiliations

  1. College of Computer and Information Science, Southwest University, Chongqing, 400715, China

    Dan Wang & Zili Zhang

Authors
  1. Dan Wang
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  2. Zili Zhang
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Corresponding author

Correspondence to Zili Zhang .

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Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Wang, D., Zhang, Z. (2021). A Novel Physarum-Based Optimization Algorithm for Shortest Path. In: Tan, Y., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2021. Lecture Notes in Computer Science(), vol 12689. Springer, Cham. https://doi.org/10.1007/978-3-030-78743-1_9

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  • DOI: https://doi.org/10.1007/978-3-030-78743-1_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78742-4

  • Online ISBN: 978-3-030-78743-1

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