Composing Fifth Species Counterpoint Music With Variable Neighborhood Search
In this paper, a variable neighborhood search (VNS) algorithm is developed and analyzed that can generate fifth species counterpoint fragments. The existing species counterpoint rules are quantified and form the basis of the objective function used by the algorithm. The VNS developed in this research is a local search metaheuristic that starts from a randomly generated fragment and gradually improves this solution by changing one or two notes at a time. An in-depth statistical analysis reveals the significance as well as the optimal settings of the parameters of the VNS. The algorithm has been implemented in a user-friendly software environment called Optimuse. Optimuse allows a user to input basic characteristics such as length, key and mode. Based on this input, a fifth species counterpoint fragment is generated that can be edited and played back immediately. This work is the expansion of a previous paper by the authors in which first species counterpoint music is composed by a similar VNS algorithm.
|Date of creation:||Sep 2012|
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Web page: https://www.uantwerp.be/en/faculties/applied-economic-sciences/
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- Avanthay, Cedric & Hertz, Alain & Zufferey, Nicolas, 2003. "A variable neighborhood search for graph coloring," European Journal of Operational Research, Elsevier, vol. 151(2), pages 379-388, December.
- Fleszar, Krzysztof & Hindi, Khalil S., 2004. "Solving the resource-constrained project scheduling problem by a variable neighbourhood search," European Journal of Operational Research, Elsevier, vol. 155(2), pages 402-413, June.
- Aguilera, Gabriel & Luis Galán, José & Madrid, Rafael & Martínez, Antonio Manuel & Padilla, Yolanda & Rodríguez, Pedro, 2010. "Automated generation of contrapuntal musical compositions using probabilistic logic in Derive," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(6), pages 1200-1211.
- Hansen, Pierre & Mladenovic, Nenad, 2001. "Variable neighborhood search: Principles and applications," European Journal of Operational Research, Elsevier, vol. 130(3), pages 449-467, May.
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