Azzato, Jeffrey D. and Krawczyk, Jacek (2007): Using a finite horizon numerical optimisation method for a periodic optimal control problem.

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Abstract
Computing a numerical solution to a periodic optimal control problem is difficult. A method of approximating a solution to a given (stochastic) optimal control problem using Markov chains was developed in [3]. This paper describes an attempt at applying this method to a periodic optimal control problem introduced in [2].
Item Type:  MPRA Paper 

Institution:  Victoria University of Wellington 
Original Title:  Using a finite horizon numerical optimisation method for a periodic optimal control problem 
Language:  English 
Keywords:  Computational techniques; Economic software; Computational methods in stochastic optimal control; Computational economics; Approximating Markov decision chains 
Subjects:  C  Mathematical and Quantitative Methods > C6  Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C63  Computational Techniques; Simulation Modeling C  Mathematical and Quantitative Methods > C8  Data Collection and Data Estimation Methodology; Computer Programs > C87  Econometric Software 
Item ID:  2298 
Depositing User:  Jeffrey Azzato 
Date Deposited:  17. Mar 2007 
Last Modified:  18. Feb 2013 06:02 
References:  J.D. Azzato and J.B. Krawczyk. SOCSol4L: An improved MATLAB package for approximating the solution to a continuoustime stochastic optimal control problem. School of Economics and Finance, VUW, 2006. MPRA: 1179; available at: http://mpra.ub.unimuenchen.de/1179/ on 14/02/2007. V. Gaitsgory and S. Rossamakhine. Linear programming approach to deterministic long run average problems of optimal control. SIAM J. Control Optim., 44:2006–2037, 2006. J.B. Krawczyk. A Markovian approximated solution to a portfolio management problem. Inf. Technol. Econ. Manag., 1, 2001. Available at: http://www.item.woiz.polsl.pl/issue/journal1.htm on 14/02/2007. 
URI:  http://mpra.ub.unimuenchen.de/id/eprint/2298 