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A Hybrid Diploid Genetic Based Algorithm for Solving the Generalized Traveling Salesman Problem

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Hybrid Artificial Intelligent Systems (HAIS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10334))

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Abstract

In this paper, we are addressing the generalized traveling salesman problem, denoted by GTSP, which is a variant of the classical traveling salesman problem (TSP). The GTSP is characterized by the fact that the vertices of the graph are partitioned into a given number of clusters and we are looking for the minimum cost tour that visits exactly one vertex from each cluster. The goal of this paper is to present a novel method for solving the GTSP, namely a hybrid diploid genetic based algorithm. The preliminary computational results on an often set of benchmark instances show that our proposed approach provides competitive solutions compared to the existing state-of-the-arts methods for solving the GTSP.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, North University Center at Baia Mare, Technical University of Cluj-Napoca, Baia Mare, Romania

    Petrica Pop, Matei Oliviu & Cosmin Sabo

Authors
  1. Petrica Pop
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  2. Matei Oliviu
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  3. Cosmin Sabo
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Corresponding author

Correspondence to Petrica Pop .

Editor information

Editors and Affiliations

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

    Francisco Javier Martínez de Pisón

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

    Rubén Urraca

  3. University of A Coruña , Ferrol, La Coruña, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Pop, P., Oliviu, M., Sabo, C. (2017). A Hybrid Diploid Genetic Based Algorithm for Solving the Generalized Traveling Salesman Problem. In: Martínez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_13

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  • DOI: https://doi.org/10.1007/978-3-319-59650-1_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59649-5

  • Online ISBN: 978-3-319-59650-1

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