Stochastic Models in Operations Research, Vol. II: Stochastic Optimization

by Daniel P. Heyman, Matthew J. Sobel

The first of a two-volume set begins with discussions of stochastic processes, including posterity analysis, birth-and-death processes, renewal theory, renewal-reward and regenerative processes, Markov chains, continuous-time Markov chains, Markov processes, and stationery processes and ergodic theory. Its coverage of operating characteristics of stochastic systems examines system properties, networks of queues, and bounds and approximations.
This two-volume set of texts explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. They demonstrate the interdependence of three areas of study that usually receive separate stochastic processes, operating characteristics of stochastic systems, and stochastic optimization.
Comprehensive in its scope, this work emphasizes the practical importance, intellectual stimulation, and mathematical elegance of stochastic models. It is intended primarily as a graduate-level text for studies in operations research, management science, computer science, and all branches of engineering, applied mathematics, statistics, and economics.

576 pages, Paperback

First published December 19, 2003