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An optimization algorithm inspired by social creativity systems
Authors:Roman Anselmo Mora-Gutiérrez  Javier Ramírez-Rodríguez  Eric Alfredo Rincón-García  Antonin Ponsich  Oscar Herrera
Affiliation:1. Posgrado de Ingeniería, Universidad Nacional Autónoma de México, C.P. 04360, Mexico, D.F., Mexico
2. Departamento de Sistemas, Universidad Autónoma Metropolitana, C.P. 02200, Mexico, D.F., Mexico
3. LIA Université d’Avignon et des Pays de Vaucluse, Avignon Cedex, France
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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