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Universal Swarm Optimizer for Multi-objective Functions

  • Luis A. Márquez-Vega
  • Luis M. Torres-TreviñoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Multi-objective optimization Zone-based model Swarm intelligence 

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Luis A. Márquez-Vega
    • 1
  • Luis M. Torres-Treviño
    • 1
    Email author
  1. 1.Facultad de Ingeniería Mecánica y EléctricaUniversidad Autónoma de Nuevo LeónSan Nicolás de los GarzaMexico

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