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A Two-Level Hybrid Based Genetic Algorithm to Solve the Clustered Shortest-Path Tree Problem Using the Prüfer Code

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Hybrid Artificial Intelligent Systems (HAIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13469))

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Abstract

The clustered shortest-path tree (CluSPT) problem is a generalization of the popular shortest path problem, in which, given a graph with the set of vertices divided into a given set of clusters, we look for a shortest-path spanning tree from a predefined source vertex to all the other vertices of the graph, with the property that every cluster should generate a connected subgraph. In this paper, we describe a two-level hybrid algorithm to solve the CluSPT problem, in which a framework with a macro-level genetic algorithm (GA) used to generate trees connecting the clusters using Prüfer code, is combined with a micro-level algorithm based on dynamic programming (DP) that determines the best corresponding feasible solution of the CluSPT problem associated to a given tree spanning the clusters. Finally, some preliminary computational results are stated on a set of 40 standard benchmark non-euclidean instances from the literature to illustrate the performance of our developed two-level hybrid algorithm. The obtained computational results demonstrate that our novel hybrid algorithm is highly competitive against the existing algorithms.

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Author information

Authors and Affiliations

  1. Technical University of Cluj-Napoca, Cluj-Napoca, Romania

    Adrian Petrovan, Petrică C. Pop, Cosmin Sabo & Ioana Zelina

  2. North University Center of Baia Mare, Dr. V. Babes 62A, 430083, Baia Mare, Romania

    Adrian Petrovan, Petrică C. Pop, Cosmin Sabo & Ioana Zelina

Authors
  1. Adrian Petrovan
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  2. Petrică C. Pop
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  3. Cosmin Sabo
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  4. Ioana Zelina
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Corresponding author

Correspondence to Petrică C. Pop .

Editor information

Editors and Affiliations

  1. University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of León, León, Spain

    Hilde Pérez García

  3. University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  4. University of Oviedo, Oviedo, Spain

    José Ramón Villar Flecha

  5. Data Science and Big Data Analytics Lab, Pablo de Olavide University, Sevilla, Spain

    Alicia Troncoso Lora

  6. Department of Computer Science, University of Oviedo, Oviedo, Spain

    Enrique A. de la Cal

  7. Applied Computational Intelligence, University of Burgos, Burgos, Burgos, Spain

    Álvaro Herrero

  8. Universidad Pablo de Olavide, Seville, Spain

    Francisco Martínez Álvarez

  9. DIGIP, University of Bergamo, Dalmine, Bergamo, Italy

    Giuseppe Psaila

  10. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  11. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Petrovan, A., Pop, P.C., Sabo, C., Zelina, I. (2022). A Two-Level Hybrid Based Genetic Algorithm to Solve the Clustered Shortest-Path Tree Problem Using the Prüfer Code. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2022. Lecture Notes in Computer Science(), vol 13469. Springer, Cham. https://doi.org/10.1007/978-3-031-15471-3_28

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  • DOI: https://doi.org/10.1007/978-3-031-15471-3_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15470-6

  • Online ISBN: 978-3-031-15471-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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