Near Optimization of Stochastic Dynamic Systems by Decomposition and Aggregation

Optimal Control Applications and Methods, Vol. 22, pp. 333–350, 2001

18 Pages Posted: 24 Jun 2009 Last revised: 25 May 2017

See all articles by Suresh Sethi

Suresh Sethi

University of Texas at Dallas - Naveen Jindal School of Management

Qing Zhang

University of Georgia - Department of Mathematics

Date Written: 2001

Abstract

The paper is concerned with the reduction of a class of stochastic optimal control problems to simpler problems by using decomposition and aggregation. Decomposition is shown to provide a good approximation when the system dynamics involve nearly decomposable matrices or variables with strong and weak interactions. Aggregation provides a good approximation if each decomposed matrix has one or more dominant eigenvalues. It is shown how one can construct nearly optimal controls for the given system from the optimal solutions of the simpler reduced problems. The results extend the corresponding results obtained in a deterministic environment. The results hold a significant promise in dealing with large dynamic stochastic macroeconomic problems.

Keywords: optimal control, dynamical system, decomposition and aggregation

JEL Classification: C61, M11, E1

Suggested Citation

Sethi, Suresh and Zhang, Qing, Near Optimization of Stochastic Dynamic Systems by Decomposition and Aggregation (2001). Optimal Control Applications and Methods, Vol. 22, pp. 333–350, 2001. Available at SSRN: https://ssrn.com/abstract=1421880

Suresh Sethi (Contact Author)

University of Texas at Dallas - Naveen Jindal School of Management ( email )

800 W. Campbell Road, SM30
Richardson, TX 75080-3021
United States

Qing Zhang

University of Georgia - Department of Mathematics ( email )

Athens, GA 30602
United States
(706) 542-2616 (Phone)
(706) 542-2573 (Fax)

HOME PAGE: http://www.math.uga.edu/~qingz/

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