An Evolutionary Approach to Computer-Aided Orchestration
In this paper we introduce an hybrid evolutionary algorithm for computer-aided orchestration. Our current approach to orchestration consists in replicating a target sound with a set of instruments sound samples. We show how the orchestration problem can be viewed as a multi-objective 0/1 knapsack problem, with additional constraints and a case-specific criteria formulation. Our search method hybridizes genetic search and local search, for both of which we define ad-hoc genetic and neighborhood operators. A simple modelling of sound combinations is used to create two new mutation operators for genetic search, while a preliminary clustering procedure allows for the computation of sound mixtures neighborhoods for the local search phase. We also show in which way user interaction might be introduced in the orchestration procedure itself, and how to lead the search according to the users choices.
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