Probability Models in Operations Research
Industrial engineering has expanded from its origins in manufacturing to transportation, health care, logistics, services, and more. A common denominator among all these industries, and one of the biggest challenges facing decision-makers, is the unpredictability of systems. Probability Models in Operations Research provides a comprehensive overview of the probabilistic and stochastic modeling approaches commonly used to capture the randomness in industrial and systems engineering.
1132942080
Probability Models in Operations Research
Industrial engineering has expanded from its origins in manufacturing to transportation, health care, logistics, services, and more. A common denominator among all these industries, and one of the biggest challenges facing decision-makers, is the unpredictability of systems. Probability Models in Operations Research provides a comprehensive overview of the probabilistic and stochastic modeling approaches commonly used to capture the randomness in industrial and systems engineering.
86.99 In Stock
Probability Models in Operations Research

Probability Models in Operations Research

Probability Models in Operations Research

Probability Models in Operations Research

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$86.99 
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Overview

Industrial engineering has expanded from its origins in manufacturing to transportation, health care, logistics, services, and more. A common denominator among all these industries, and one of the biggest challenges facing decision-makers, is the unpredictability of systems. Probability Models in Operations Research provides a comprehensive overview of the probabilistic and stochastic modeling approaches commonly used to capture the randomness in industrial and systems engineering.

Product Details

ISBN-13: 9780367387044
Publisher: Taylor & Francis
Publication date: 09/19/2019
Series: Operations Research Series
Pages: 224
Product dimensions: 6.12(w) x 9.19(h) x (d)

About the Author

Cassady, C. Richard; Nachlas, Joel A.

Table of Contents

Probability Modeling Fundamentals. Analysis of Random Variables. Analysis of Multiple Random Variables. Bernoulli Processes. Discrete-Time Markov Chains. Poisson Processes. Renewal Processes. Continuous-Time Markov Chains. Queueing Theory.

What People are Saying About This

From the Publisher

The authors used a subset of the homework problems as in-class examples and another subset for homework–an excellent idea. Each of the six chapters also contains an application illustrating how the principles discussed can be applied in real life ... another very good idea. Overall, this clearly written work is a useful resource ... Summing Up: Highly recommended.
– R. Bharath, Emeritus, Northern Michigan University, in Choice: Current Reviews for Academic Libraries, Vol. 47, No. 1

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