John Wiley & Sons Introduction to Stochastic Processes and Simulation Cover Mastering chance has, for a long time, been a preoccupation of mathematical research. Today, we poss.. Product #: 978-1-78630-484-1 Regular price: $132.71 $132.71 Auf Lager

Introduction to Stochastic Processes and Simulation

Cochard, Gerard-Michel

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1. Auflage November 2019
310 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-78630-484-1
John Wiley & Sons

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Mastering chance has, for a long time, been a preoccupation of mathematical research. Today, we possess a predictive approach to the evolution of systems based on the theory of probabilities. Even so, uncovering this subject is sometimes complex, because it necessitates a good knowledge of the underlying mathematics.This book offers an introduction to the processes linked to the fluctuations in chance and the use of numerical methods to approach solutions that are difficult to obtain through an analytical approach.It takes classic examples of inventory and queueing management, and addresses more diverse subjects such as equipment reliability, genetics, population dynamics, physics and even market finance. It is addressed to those at Master s level, at university, engineering school or management school, but also to an audience of those in continuing education, in order that they may discover the vast field of decision support.

Part 1. Basic Mathematical Concepts1. Basic Reminders of Probability.2. Probabilistic Models.3. Inventory Management.Part 2. Stochastic Processes4. Markov Chains.5. Markov Processes.6. Queueing Systems.7. Various Applications.Part 3. Simulation8. Generator Programs.9. Principles of Simulation.10. Simulation of Inventory Management.11. Simulation of a Queueing Process.12. Optimization and Simulation.
Gerard-Michel Cochard was made an Emeritus Professor at the University of Picardie Jules Verne, Amiens, France. In the past he held many responsibilities at National Conservatory of Arts and Crafts (CNAM) and the Ministry of National Education. At present, he researches within the Eco-Processes, Optimization and Decision Support (EPROAD) Laboratory at the University of Picardie Jules Verne.