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.

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.

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.

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.