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International Conference On Big Data and Internet of Things

BDIoT 2021: Proceedings of the 5th International Conference on Big Data and Internet of Things pp 48–58Cite as

A Fuzzy Meta Model for Adjusting Ant Colony System Parameters

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 489))

Abstract

Metaheuristic algorithms have become an important choice for solving complex optimization problems which are difficult to solve by conventional methods. But, like many other metaheuristic algorithms, ant colony system (ACS) has the problem of parameters setting. In the last few years, different approaches have been proposed to deal whit this problem. Recently the use of fuzzy logic in dynamic parameters adaptation of metaheuristic algorithms is gaining a considerable interest from the researchers. In this paper, a meta model for modifying the parameters of ACS during runtime based on fuzzy logic concept is presented. The main idea is to study the effect of modifying all the parameters of the ACS on the same time on its performance. To compare the efficiency of the proposed approaches, they were applied to a set of traveling salesman problem instances. Also, a comparison with the standard ACS and some literature results are discussed.

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Author information

Authors and Affiliations

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

    Safae Bouzbita & Abdellatif El Afia

Authors
  1. Safae Bouzbita
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  2. Abdellatif El Afia
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Corresponding author

Correspondence to Safae Bouzbita .

Editor information

Editors and Affiliations

  1. ENSIAS, Mohammed V University, Rabat, Morocco

    Mohamed Lazaar

  2. UNILEHAVRE, UNIROUEN, Normandie Université, Le Havre, France

    Claude Duvallet

  3. Vrije Universiteit Brussel, Brussels, Belgium

    Abdellah Touhafi

  4. ENSA, Abdelmalek Essaâdi University, Tetuan, Morocco

    Mohammed Al Achhab

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Bouzbita, S., Afia, A.E. (2022). A Fuzzy Meta Model for Adjusting Ant Colony System Parameters. In: Lazaar, M., Duvallet, C., Touhafi, A., Al Achhab, M. (eds) Proceedings of the 5th International Conference on Big Data and Internet of Things. BDIoT 2021. Lecture Notes in Networks and Systems, vol 489. Springer, Cham. https://doi.org/10.1007/978-3-031-07969-6_4

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