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An optimization algorithm inspired by social creativity systems
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AI
DOI：10.1007/s00607-012-0205-0.png)
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Abstract
En 中文
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-Guti,rrez 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.
Keywords:
Global optimization
Metaheuristics
Social algorithms
Socio-cultural system of creativity
Musical composition
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