Direct optimization using Gaussian quadrature and continuous Runge-Kutta methods: Application to an innovation diffusion model

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Abstract

In the present paper the discretization of a particular model arising in the economic field of innovation diffusion is developed. It consists of an optimal control problem governed by an ordinary differential equation. We propose a direct optimization approach characterized by an explicit, fixed step-size continuous Runge-Kutta integration for the state variable approximation. Moreover, high-order Gaussian quadrature rules are used to discretize the objective function. In this way, the optimal control problem is converted into a nonlinear programming one which is solved by means of classical algorithms. © Springer-Verlag Berlin Heidelberg 2004.

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Diele, F., Marangi, C., & Ragni, S. (2004). Direct optimization using Gaussian quadrature and continuous Runge-Kutta methods: Application to an innovation diffusion model. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3039, 426–433. https://doi.org/10.1007/978-3-540-25944-2_56

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