A Genetic Algorithm Compared with a Gradient-Based Method for the Solution of an Active-Control Model Problem

Abstract : In this study, a linear active-control model problem is employed to conduct a preliminary performance comparison between a genetic algorithm and a classical optimization method based on the evaluation of a gradient of functional. For this purpose, we consider a system modeled by the heat equation in one space dimension controled by a source term. The cost functional is a quadratic form of the distance between the final state and a prescribed function augmented of a penalty involving the control quadratically. The problem is first solved by a direct identification of the «optimal-control law» from the solution of a Riccati system. A simple genetic algorithm is implemented afterwards and compared.
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RR-2948, INRIA. 1996
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Nathalie Marco, Cyril Godart, Jean-Antoine Desideri, Bertrand Mantel, Jacques Périaux. A Genetic Algorithm Compared with a Gradient-Based Method for the Solution of an Active-Control Model Problem. RR-2948, INRIA. 1996. 〈inria-00073751〉

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