Computing average optimal constrained policies in stochastic dynamic programming

Computing average optimal constrained policies in stochastic dynamic programming

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Article ID: iaor20023452
Country: United States
Volume: 15
Issue: 1
Start Page Number: 103
End Page Number: 133
Publication Date: Jan 2001
Journal: Probability in the Engineering and Informational Sciences
Authors:
Abstract:

A stochastic dynamic program incurs two types of cost: a service cost and a quality of service (delay) cost. The objective is to minimize the expected average service cost, subject to a constraint on the average quality of service cost. When the state space S is finite, we show how to compute an optimal policy for the general constrained problem under weak conditions. The development uses a Lagrange multiplier approach and value iteration. When S is denumerably infinite, we give a method for computation of an optimal policy, using a sequence of approximating finite state problems. The method is illustrated with two computational examples.

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