http://www.cnr.it/ontology/cnr/individuo/prodotto/ID7813
Direct Optimization Using Gaussian Quadrature and Continuous Runge-Kutta Methods: Application to an Innovation Diffusion Model (Articolo in rivista)
- Type
- Label
- Direct Optimization Using Gaussian Quadrature and Continuous Runge-Kutta Methods: Application to an Innovation Diffusion Model (Articolo in rivista) (literal)
- Anno
- 2004-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- Alternative label
Diele F., Marangi C., Ragni S. (2004)
Direct Optimization Using Gaussian Quadrature and Continuous Runge-Kutta Methods: Application to an Innovation Diffusion Model
in Lecture notes in computer science; Springer, Berlin (Germania)
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Diele F., Marangi C., Ragni S. (literal)
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- http://www.springerlink.com/content/q7yhjkbc2hdr21c9/fulltext.pdf (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Fasma Diele, Istituto per le Applicazioni del Calcolo M. Picone,CNR, Via Amendola 122, 70126 Bari, Italy;
Carmela Marangi, Istituto per le Applicazioni del Calcolo M. Picone,CNR, Via Amendola 122, 70126 Bari, Italy;
Stefania Ragni, Facoltà di Economia, Università di Bari, Via Camillo Rosalba 56, 70100 Bari, Italy (literal)
- Titolo
- Direct Optimization Using Gaussian Quadrature and Continuous Runge-Kutta Methods: Application to an Innovation Diffusion Model (literal)
- 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. (literal)
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