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Cost rate heuristics for semi-Markov decision processes

Published online by Cambridge University Press:  14 July 2016

K. D. Glazebrook*
Affiliation:
University of Newcastle upon Tyne
Michael P. Bailey*
Affiliation:
Naval Postgraduate School, Monterey
Lyn R. Whitaker*
Affiliation:
Naval Postgraduate School, Monterey
*
∗ Postal address: Department of Mathematics and Statistics, The University, Newcastle upon Tyne NE1 7RU, UK.
∗∗ Postal address: Department of Operations Research, Naval Postgraduate School, Monterey, CA 93943, USA.
∗∗ Postal address: Department of Operations Research, Naval Postgraduate School, Monterey, CA 93943, USA.

Abstract

In response to the computational complexity of the dynamic programming/backwards induction approach to the development of optimal policies for semi-Markov decision processes, we propose a class of heuristics resulting from an inductive process which proceeds forwards in time. These heuristics always choose actions in such a way as to minimize some measure of the current cost rate. We describe a procedure for calculating such cost rate heuristics. The quality of the performance of such policies is related to the speed of evolution (in a cost sense) of the process. A simple model of preventive maintenance is described in detail. Cost rate heuristics for this problem are calculated and assessed computationally.

MSC classification

Information

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1992 

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