Abstract
In this paper we present new components to be included in harmony search algorithms. These components are inspired from music improvisation. The Modal improvisation uses musical modes rather than chord progressions as a harmonic framework. We also include the notion of tone scales that allows the algorithm to visit different parts of the search space. We evaluate our approach solving instances of the Multidimensional Knapsack Problem instances. We compare our results with those obtained by the former harmony search algorithm, and with the well-known state-of-the-art results.
This work is partially supported by FONDECYT Project 1120781 and Centro Científico Tecnológico de Valparaíso (CCT-Val) FB0821.
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References
Geem, Z.W., Kim, J.H., Loganathan, G.: A new heuristic optimization algorithm: harmony search. Simulation 76(2), 60–68 (2001)
Geem, Z.W. (ed.): Music-Inspired Harmony Search Algorithm. Studies in Computational Intelligence, vol. 191. Springer, Heidelberg (2009)
Riff, M.C., Montero, E.: A new algorithm for reducing metaheuristic design effort. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2013), pp. 3283–3290 (2013)
Yang, X.-S.: Harmony search as a metaheuristic algorithm. In: Geem, Z.W. (ed.) Music-Inspired Harmony Search Algorithm. Studies in Computational Intelligence, vol. 191, pp. 1–14. Springer, Heidelberg (2009)
Lee, K.S., Geem, Z.W.: A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Computer Methods in Applied Mechanics and Engineering 194(36), 3902–3933 (2005)
Wang, L., Yang, R., Xu, Y., Niu, Q., Pardalos, P.M., Fei, M.: An improved adaptive binary harmony search algorithm. Information Sciences 232, 58–87 (2013)
Wang, L., Xu, Y., Mao, Y., Fei, M.: A discrete harmony search algorithm. In: Li, K., Li, X., Ma, S., Irwin, G.W. (eds.) LSMS 2010. CCIS, vol. 98, pp. 37–43. Springer, Heidelberg (2010)
Alia, O., Mandava, R.: The variants of the harmony search algorithm: an overview. Artificial Intelligence Review 36(1), 49–68 (2011)
Monson, I.: Oh freedom: George russell, john coltrane, and modal jazz. The Course of Performance: Studies in the World of Musical Improvisation, 149–68 (1998)
Pease, F., Mattingly, R.: Jazz composition: theory and practice. Berklee Press (2003)
Rossi-Doria, O., et al.: A Comparison of the Performance of Different Metaheuristics on the Timetabling Problem. In: Burke, E.K., De Causmaecker, P. (eds.) PATAT 2002. LNCS, vol. 2740, pp. 329–351. Springer, Heidelberg (2003)
Bartz-Beielstein, T.: Experimental research in evolutionary computation. Springer, Berlin (2006)
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Rojas, N., Riff, MC. (2013). Including Modal Improvisation and Music-Inspired Components to Improve Harmony Search. In: Castro, F., Gelbukh, A., González, M. (eds) Advances in Soft Computing and Its Applications. MICAI 2013. Lecture Notes in Computer Science(), vol 8266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45111-9_9
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DOI: https://doi.org/10.1007/978-3-642-45111-9_9
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