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An optimization algorithm inspired by social creativity systems

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Abstract

The need for efficient and effective optimization problem solving methods arouses nowadays the design and development of new heuristic algorithms. This paper present ideas that leads to a novel multiagent metaheuristic technique based on creative social systems suported on music composition concepts. This technique, called “Musical Composition Method” (MMC), which was proposed in Mora-Gutiérrez et al. (Artif Intell Rev 2012) as well as a variant, are presented in this study. The performance of MMC is evaluated and analyzed over forty instances drawn from twenty-two benchmark global optimization problems. The solutions obtained by the MMC algorithm were compared with those of various versions of particle swarm optimizer and harmony search on the same problem set. The experimental results demonstrate that MMC significantly improves the global performances of the other tested metaheuristics on this set of multimodal functions.

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Authors and Affiliations

  1. Posgrado de Ingeniería, Universidad Nacional Autónoma de México, C.P. 04360 , Mexico, D.F., Mexico

    Roman Anselmo Mora-Gutiérrez

  2. Departamento de Sistemas, Universidad Autónoma Metropolitana, C.P. 02200 , Mexico, D.F., Mexico

    Javier Ramírez-Rodríguez, Eric Alfredo Rincón-García, Antonin Ponsich & Oscar Herrera

  3. LIA Université d’Avignon et des Pays de Vaucluse, Avignon Cedex, France

    Javier Ramírez-Rodríguez

Authors
  1. Roman Anselmo Mora-Gutiérrez
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  2. Javier Ramírez-Rodríguez
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  3. Eric Alfredo Rincón-García
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  4. Antonin Ponsich
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  5. Oscar Herrera
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Correspondence to Roman Anselmo Mora-Gutiérrez.

Appendix

Appendix

See Tables 11, 12 and 13.

Table 11 Results first experiment (mean \(\pm \) standard deviation)
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Table 12 Results of second experiment (mean \(\pm \) standard deviation)
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Table 13 Results of third experiment (mean \(\pm \) standard deviation)
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Mora-Gutiérrez, R.A., Ramírez-Rodríguez, J., Rincón-García, E.A. et al. An optimization algorithm inspired by social creativity systems. Computing 94, 887–914 (2012). https://doi.org/10.1007/s00607-012-0205-0

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