Journal of Heuristics

, Volume 16, Issue 5, pp 681–714 | Cite as

Solving the musical orchestration problem using multiobjective constrained optimization with a genetic local search approach

  • Grégoire Carpentier
  • Gérard Assayag
  • Emmanuel Saint-James


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.


Orchestration Computer-aided composition Computer music Compositional algorithms Multiobjective combinatorial optimization Evolutionary algorithms Global constraints Local search CDCSolver 


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Grégoire Carpentier
    • 1
  • Gérard Assayag
    • 1
  • Emmanuel Saint-James
    • 2
  1. 1.IRCAMParisFrance
  2. 2.LIP6Paris Cedex 05France

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