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Adjusting Population Size of Ant Colony System Using Fuzzy Logic Controller

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Computational Collective Intelligence (ICCCI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11684))

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Abstract

The population size has a very strong impact on the efficiency, solution quality, and computational cost in a Swarm Intelligence (SI). In Ant Colony System algorithm, and as a Swarm Intelligence and population size based algorithm, the number of ants plays a very important role in directing the colony toward a high quality solution within a reasonable time. In this paper, a Fuzzy Logic strategy for adjusting the number of ants during runtime is presented. The based indicators for this adjustment are: Iteration and Convergence Rate. Some experiments are conducted using Travelling Salesman Problems, and results show that modifying the number of ants has a crucial effect on the performance of the Ant Colony System algorithm especially on the quality of solution.

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Authors and Affiliations

  1. Smart Systems Laboratory, ENSIAS - Mohammed V University, Rabat, Morocco

    Safae Bouzbita, Abdellatif El Afia & Rdouan Faizi

Authors
  1. Safae Bouzbita
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  2. Abdellatif El Afia
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  3. Rdouan Faizi
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Corresponding author

Correspondence to Safae Bouzbita .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. University of Pau and Pays de l'Adour, Pau, France

    Richard Chbeir

  3. University of Pau and Pays de l'Adour, Pau, France

    Ernesto Exposito

  4. University of Pau and Pays de l'Adour, Pau, France

    Philippe Aniorté

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Bouzbita, S., El Afia, A., Faizi, R. (2019). Adjusting Population Size of Ant Colony System Using Fuzzy Logic Controller. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11684. Springer, Cham. https://doi.org/10.1007/978-3-030-28374-2_27

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  • DOI: https://doi.org/10.1007/978-3-030-28374-2_27

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  • Print ISBN: 978-3-030-28373-5

  • Online ISBN: 978-3-030-28374-2

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