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International Conference on Advanced Information Technology, Services and Systems

AIT2S 2017: Advanced Information Technology, Services and Systems pp 461–473Cite as

Hybrid Penguins Search Optimization Algorithm and Genetic Algorithm Solving Traveling Salesman Problem

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 25))

Abstract

This paper is to present a hybrid technique of two metaheuristic algorithm Penguins Search optimization Algorithm (PeSOA) and the genetic algorithm (GA) called HPeSOA, which was proposed to solve the combinatorial optimization problem NP-hard Traveling salesman problem. In this algorithm, we improve the population of the solutions by the integration of the genetic operators, namely the crossover and the mutation in the algorithm PeSOA. The experimental results of the application of HPeSOA algorithm on the instances TSPLIB are reported and compared, with the results of Penguins Search optimization Algorithm and the genetic algorithm.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Faculty of Sciences, Chouaïb Doukkali University, El Jadida, Morocco

    Ilyass Mzili & Mohammed Essaid Riffi

  2. Department of Mathematics, Faculty of Sciences, Chouaïb Doukkali University, El Jadida, Morocco

    Fatiha Benzekri

Authors
  1. Ilyass Mzili
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  2. Mohammed Essaid Riffi
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  3. Fatiha Benzekri
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Corresponding author

Correspondence to Ilyass Mzili .

Editor information

Editors and Affiliations

  1. Faculty of Sciences and Technologies, Tangier, Morocco

    Mostafa Ezziyyani

  2. Faculty of Sciences and Technologies, University Hassan 1st, Settat, Morocco

    Mohamed Bahaj

  3. Faculty of Sciences and Technologies, Mohammedia, Morocco

    Faddoul Khoukhi

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Mzili, I., Riffi, M.E., Benzekri, F. (2018). Hybrid Penguins Search Optimization Algorithm and Genetic Algorithm Solving Traveling Salesman Problem. In: Ezziyyani, M., Bahaj, M., Khoukhi, F. (eds) Advanced Information Technology, Services and Systems. AIT2S 2017. Lecture Notes in Networks and Systems, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-69137-4_41

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  • DOI: https://doi.org/10.1007/978-3-319-69137-4_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69136-7

  • Online ISBN: 978-3-319-69137-4

  • eBook Packages: EngineeringEngineering (R0)

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