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A Binary Ant Lion Optimisation Algorithm Applied to the Set Covering Problem

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Artificial Intelligence Methods in Intelligent Algorithms (CSOC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 985))

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Abstract

The study and understanding of algorithms that solve combinatorial problems based on swarm intelligence continuous metaheuristics, is an area of interest at the level of basic and applied science. This is due to the fact that many of the problems addressed at industrial level are of a combinatorial type and a subset no less than these are of the NP-hard type. In this article, a mechanism of binarization of continuous metaheuristics that uses the concept of the percentile is proposed. This percentile concept is applied to the An Lion optimization algorithm, solving the set covering problem (SCP). Experiments were designed to demonstrate the importance of the percentile concept in the binarization process. Subsequently, the efficiency of the algorithm is verified through reference instances. The results indicate that the binary Ant Lion Algorithm (BALO) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

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Authors and Affiliations

  1. School of Engineering, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile

    Lorena Jorquera, Pamela Valenzuela, Matías Valenzuela & Hernan Pinto

Authors
  1. Lorena Jorquera
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  2. Pamela Valenzuela
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  3. Matías Valenzuela
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  4. Hernan Pinto
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Corresponding author

Correspondence to Matías Valenzuela .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Jorquera, L., Valenzuela, P., Valenzuela, M., Pinto, H. (2019). A Binary Ant Lion Optimisation Algorithm Applied to the Set Covering Problem. In: Silhavy, R. (eds) Artificial Intelligence Methods in Intelligent Algorithms. CSOC 2019. Advances in Intelligent Systems and Computing, vol 985. Springer, Cham. https://doi.org/10.1007/978-3-030-19810-7_16

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