Wiley series in probability and statistics. Applied probability and statistics section
"A Wiley-Interscience publication."
Includes bibliographical references (pages 316-323) and index.
Optimization criteria -- Finite horizon optimization -- Infinite horizon discounted cost optimization -- An inventory model -- Average cost optimization for finite state spaces -- Average cost optimization theory for countable state spaces -- Computation of average cost optimal policies for infinite state spaces -- Optimization under actions at selected epochs -- Average cost optimization of continuous time processes -- Appendices -- Bibliography -- Index.
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Stochastic Dynamic Programming and the Control of Queueing Systems presents the theory of optimization under the finite horizon, infinite horizon discounted, and average cost criteria. It then shows how optimal rules of operation (policies) for each criterion may be numerically determined. A great wealth of examples from the application area of the control of queueing systems is presented. Nine numerical programs for the computation of optimal policies are fully explicated.
This book's clear presentation of theory, numerous chapter-end problems, and development of a unified method for the computation of optimal policies in both discrete and continuous time make it an excellent course text for graduate students and advanced undergraduates. Its comprehensive coverage of important recent advances in stochastic dynamic programming makes it a valuable working resource for operations research professionals, management scientists, engineers, and others.
Stochastic dynamic programming and the control of queueing systems.