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)


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.


Multi-objective optimization Zone-based model Swarm intelligence 


  1. 1.
    Coello, C.A.C., Pulido, G.T., Lechuga, M.S.: Handling multiple objectives with particle swarm optimization. IEEE Trans. Evol. Comput. 8(3), 256–279 (2004). Scholar
  2. 2.
    Couzin, I., Krause, J., James, R., Ruxton, G., Franks, N.: Collective memory and spatial sorting in animal groups. J. Theor. Biol. 218(1), 1–11 (2002)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Samaei, F., Bashiri, M., Tavakkoli-Moghaddam, R.: A comparison of four multi-objective meta-heuristics for a capacitated location-routing problem. J. Ind Syst. Eng. 6, 20–33 (2012)Google Scholar
  4. 4.
    Kolpas, A., Busch, M., Li, H., Couzin, I.D., Petzold, L., Moehlis, J.: How the spatial position of individuals affects their influence on swarms: a numerical comparison of two popular swarm dynamics models. PLoS ONE 8 (2013)CrossRefGoogle Scholar
  5. 5.
    Mirjalili, S., Saremi, S., Mirjalili, S.M., dos Santos Coelho, L.: Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Syst. Appl. 47, 106–119 (2016)CrossRefGoogle Scholar
  6. 6.
    Wolpert, D.H., Macready, W.G.: No free lunch theorems for optimization. Trans. Evol. Comput. 1(1), 67–82 (1997). Scholar
  7. 7.
    Zhang, Q., Zhou, A., Zhao, S., Suganthan, P.N., Liu, W., Tiwari, S.: Multiobjective optimization test instances for the CEC 2009 special session and competition (2009)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

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

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