Journal of the ACM (JACM)
Theoretical aspects of evolutionary computing
Tabu Search
Yet Another Local Search Method for Constraint Solving
SAGA '01 Proceedings of the International Symposium on Stochastic Algorithms: Foundations and Applications
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Computer-Assisted Composition at IRCAM: From PatchWork to OpenMusic
Computer Music Journal
Evolutionary Computer Music
EURASIP Journal on Applied Signal Processing
Enhancing orchestration technique via spectrally based linear algebra methods
Computer Music Journal
Self-organizing Bio-inspired Sound Transformation
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
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In this paper a computational approach of musical orchestration is presented. We consider orchestration as the search of relevant sound combinations within large instruments sample databases and propose two cooperating metaheuristics to solve this problem. Orchestration is seen here as a particular case of finding optimal constrained multisets on a large ensemble with respect to several objectives. We suggest a generic and easily extendible formalization of orchestration as a constrained multiobjective search towards a target timbre, in which several perceptual dimensions are jointly optimized. We introduce Orchidée, a time-efficient evolutionary orchestration algorithm that allows the discovery of optimal solutions and favors the exploration of non-intuitive sound mixtures. We also define a formal framework for global constraints specification and introduce the innovative CDCSolver repair metaheuristic, thanks to which the search is led towards regions fulfilling a set of musical-related requirements. Evaluation of our approach on a wide set of real orchestration problems is also provided.