This book provides the first simultaneous coverage of the statistical aspects of simulation and Monte Carlo methods, their commonalities and their differences for the solution of a wide spectrum of engineering and scientific problems. It contains standard material usually considered in Monte Carlo simulation as well as new material such as variance reduction techniques, regenerative simulation, and Monte Carlo optimization.
Table des matières
Systems, Models, Simulation and the Monte Carlo Method.
Random Number Generation.
Random Variate Generation.
Monte Carlo Integration and Variance Reduction Techniques.
Linear Equations and Markov Chains.
Regenerative Method for Simulation Analysis.
Monte Carlo Optimization.
Appendix.
Exercises.
References.
Index.
A propos de l’auteur
Reuven Rubinstein, Ph D, is the Chair in Industrial Engineering and Management, at Technion-Israel Institute of Technology in Haifa, Israel. He is the author of
Discrete Event Systems: Sensitivity Analysis and Stochastic Optimization,
Modern Simulation and Modeling, and
Monte Carlo Optimization, Simulation and Sensitivity of Queueing Networks, all from Wiley.
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