Stochastic Dynamic Programming and the Control of Queueing Systems

ISBN-13: 9780471161202 / Angielski / Twarda / 1998 / 354 str.

Linn Sennott;Sennott

Opis

This text covers the essentials of stochastic dynamic programming (also known as stochastic optimal control, Markov decision processes, or Markov decision chains) with a specific focus on the application of queueing theory. The text integrates both theory and computation in its discussion of stochastic dynamic programming. The theory of optimization criterion is first developed and proven before giving the computational methods to determine the numerical policies of the theory. Focusing on queueing systems allows for an in-depth exploration of the application of the outlined principles

Recenzje

There is much to appreciate about his book. It is well written and thoughtfully organized and nicely integrates theory with computation. Its orientation toward SDP theory for buffer control will certainly interest scientists seeking solutions to communication network problems. (Technometrics, August 2000, Vol. 42, No. 3)

Spis treści

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.

O autorze

Linn I. Sennott, PhD, is Professor of Mathematics at Illinois State University.

Blurb

A path–breaking account of Markov decision processes–theory and computation

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 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.

The Pascal source code for the programs is available for viewing and downloading on the Wiley Web site at www.wiley.com/products/subject/mathematics. The site contains a link to the author′s own Web site and is also a place where readers may discuss developments on the programs or other aspects of the material. The source files are also available via ftp at ftp://ftp.wiley.com/public/sci—tech—med/stochastic

Stochastic Dynamic Programming and the Control of Queueing Systems features:
∗ Path–breaking advances in Markov decision process techniques, brought together for the first time in book form
∗ A theorem/proof format (proofs may be omitted without loss of continuity)
∗ Development of a unified method for the computation of optimal rules of system operation
∗ Numerous examples drawn mainly from the control of queueing systems
∗ Detailed discussions of nine numerical programs
∗ Helpful chapter–end problems
∗ Appendices with complete treatment of background material