Stochastic Modeling: Analysis and Simulation

by Barry L. Nelson

A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Suitable for advanced undergraduates and graduate-level industrial engineers and management science majors, it proposes modeling systems in terms of their simulation, regardless of whether simulation is employed for analysis. Beginning with a view of the conditions that permit a mathematical-numerical analysis, the text explores Poisson and renewal processes, Markov chains in discrete and continuous time, semi-Markov processes, and queuing processes. Each chapter opens with an illustrative case study, and comprehensive presentations include formulation of models, determination of parameters, analysis, and interpretation of results. Programming language–independent algorithms appear for all simulation and numerical procedures.

Genres: Science, Mathematics

338 pages, Kindle Edition

First published December 1, 1994

About the author

Barry L. Nelson is the James N. and Margie M. Krebs Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University and is director of the Master of Engineering Management Program there. His research centers on the design and analysis of computer-simulation experiments on models of stochastic systems, concentrating on multivariate input modeling and output analysis and on optimization via simulation. He has published numerous papers and two books. He has served as the simulation area editor of Operations Research and as president of the INFORMS (then TIMS) College on Simulation, and he has held many positions for the annual Winter Simulation Conference, including program chair in 1997 and board member currently.