Using a finite horizon numerical optimisation method for a periodic optimal control problem

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

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
• 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

References

J.D. Azzato and J.B. Krawczyk. SOCSol4L: An improved MATLAB package for approximating the solution to a continuous-time stochastic optimal control problem. School of Economics and Finance, VUW, 2006. MPRA: 1179; available at: http://mpra.ub.uni-muenchen.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.