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Mexican International Conference on Artificial Intelligence

MICAI 2018: Advances in Soft Computing pp 50–61Cite as

Universal Swarm Optimizer for Multi-objective Functions

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11288))

Abstract

This paper presents the Universal Swarm Optimizer for Multi-Objective Functions (USO), which is inspired in the zone-based model proposed by Couzin that represents in a more realistic way the behavior of biological species as fish schools and bird flocks. The algorithm is validated using 10 multi-objective benchmark problems and a comparison with the Multi-Objective Particle Swarm Optimization (MOPSO) is presented. The obtained results suggest that the proposed algorithm is very competitive and presents interesting characteristics which could be used to solve a wide range of optimization problems.

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References

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Author information

Authors and Affiliations

  1. Facultad de Ingeniería Mecánica y Eléctrica, Universidad Autónoma de Nuevo León, Pedro de Alba s/n, 66455, San Nicolás de los Garza, Nuevo León, Mexico

    Luis A. Márquez-Vega & Luis M. Torres-Treviño

Authors
  1. Luis A. Márquez-Vega
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  2. Luis M. Torres-Treviño
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Corresponding author

Correspondence to Luis M. Torres-Treviño .

Editor information

Editors and Affiliations

  1. Instituto Politécnico Nacional, Mexico City, Mexico

    Ildar Batyrshin

  2. Universidad Panamericana, Mexico City, Mexico

    María de Lourdes Martínez-Villaseñor

  3. Faculty of Engineering, Universidad Panamericana, Mexico City, Mexico

    Hiram Eredín Ponce Espinosa

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Márquez-Vega, L.A., Torres-Treviño, L.M. (2018). Universal Swarm Optimizer for Multi-objective Functions. In: Batyrshin, I., Martínez-Villaseñor, M., Ponce Espinosa, H. (eds) Advances in Soft Computing. MICAI 2018. Lecture Notes in Computer Science(), vol 11288. Springer, Cham. https://doi.org/10.1007/978-3-030-04491-6_4

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  • DOI: https://doi.org/10.1007/978-3-030-04491-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-04490-9

  • Online ISBN: 978-3-030-04491-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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