Approximation and bounds in discrete event dynamic programming

This paper presents a general dynamic programming algorithm for the solution of optimal stochastic control problems concerning a class of discrete event systems. The emphasis is put on the numerical technique used for the approximation of the solution of the dynamic programming equation. This approach can be efficiently used for the solution of optimal control problems concerning Markov renewal processes. This is illustrated on a group preventive replacement model generalizing an earlier work of the authors.