Abstract
The constrained portfolio optimization problem with multi-objective functions cannot be efficiently solved using exact techniques. Thus, heuristics approaches seem to be the best option to find high quality solutions in a limited amount of time. For solving this problem, this paper proposes an algorithm based on the Method of Musical Composition (MMC), a metaheuristic that mimics an multi-agent based creativity system associated with musical composition. In order to prove its performance, the algorithm was tested over five well-known benchmark data sets and the obtained results prove to be highly competitive since they outperform those reported in the specialized literature in four out of the five tackled instances.
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Mora-Gutiérrez, R.A., Ponsich, A., Rincón García, E.A., de-los-Cobos-Silva, S.G., Gutiérrez Andrade, M.Á., Lara-Velázquez, P. (2017). Method of Musical Composition for the Portfolio Optimization Problem. In: Pichardo-Lagunas, O., Miranda-Jiménez, S. (eds) Advances in Soft Computing. MICAI 2016. Lecture Notes in Computer Science(), vol 10062. Springer, Cham. https://doi.org/10.1007/978-3-319-62428-0_29
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DOI: https://doi.org/10.1007/978-3-319-62428-0_29
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