Ross S. Applied Probability Models with Optimization Applications 1992 torrent

Textbook in PDF format

This text developed from a series of courses in applied probability and optimization theory given by the author at the University of California at Berkeley.
A prerequisite to its reading would be some familiarity with probability theory at the level of Volume I of Feller's well-known book.
Ideally, this book would be used as a text in a one-year course in applied probability models with optimization applications. However, because of its flexibility, it would also be suitable as a text in more specialized topics. For instance, Chapters 1 through 5 and Chapter 9 might be used in a one- or two-quarter course in applied probability or stochastic processes. Also, Chapters 6 through 9 might be used as a text for a course in sequential decision theory. It should also be mentioned that this book has been designed so as to include most of the stochastic models of operations research, and hence may be readily used as a text in this subject.
The approach I have attempted to employ in this book is to view models from a probabilistic point of view. For instance, wherever possible, proofs are based on probabilistic, rather than analytic, arguments. I feel that this approach quickly gives the student a feeling for what is essential in this subject.
Introduction to stochastic processes
The poisson process
Renewal theory
Markov chains
Semi-markov, markov renewal and regenerative processes
Markov decision processes
Semi-markov decision processes
Inventory theory
Brownian motion and continuous time optimization models
Appendices
Index