Foundations and Methods of Stochastic Simulation

This book covers modeling, programming and analysis of simulation experiments and offers a rigorous treatment of the foundations of simulation and why it works. Emphasizes lasting principles, includes end of chapter exercises and an online manual of solutions.

This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material); and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems and prepares the reader to use simulation in research as well as practice.

The book is a rigorous, but concise treatment, emphasizing lasting principles but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research; no other book does this. An online solutions manual for end of chapter exercises is also provided.

Complete graduate text for the one-semester course in Stochastic Simulation Includes end-of-chapter exercises and online solutions manual Author is one of the best-known authorities and teaches the class at Northwestern University Includes supplementary material: sn.pub/extras

Auteur
Barry L. Nelson currently serves as the Chair of the Department of Industrial Engineering and Management Sciences at Northwestern, as well as past Editor in Chief of Naval Research Logistics. He has also received an award for the Charles Deering McCormick Professor of Teaching Excellence. Barry Nelson's research is involved with the design and analysis of computer simulation experiments on models of stochastic systems, focusing particularly on issues related to statistical efficiency of simulation experiments. His research includes modeling and analysis of networks of nonstationary queues. The applications of this include computer-performance modeling, manufacturing systems, financial engineering and transportation.

Contenu
Why Do We Simulate?.- Simulation Programming: Quick Start.- Examples.- Simulation Programming with VBASim.- Two Views of Simulation.- Simulation Input.- Simulation Output.- Experiment Design and Analysis.- Simulation for Research.- VBASim.