# 10907 Stochastic Models in Operations Research 1

**Credits**: 6 advanced credits in Industrial Engineering and Management or in Sciences - General

**Prerequisites**: 36 credits, including Differential and Integral Calculus I, Differential and Integral Calculus II, one of the following: Introduction to Statistics and Probability for Science Students, Introduction to Statistics for Students of Social Sciences I, Probability for Computer Science Students. Students must also fulfill all **English** requirements and take **bibliographic instruction** in the Library.

The course is based on *Introduction to Probability Models* (8th ed.), by S.M. Ross (Academic Press, 2003).

The course provides a broad foundation for decision-making in processes occurring under uncertainty. It deepens students� theoretical knowledge of probability theory and conditional probability. Practical processes such as Markov chains and queueing systems are analyzed.

**Topics**: Introduction to probability theory; Conditional probability and its applications; Markov chains; The exponential distribution and the Poisson process; Continuous-time Markov chains; Queueing theory.

1Students may **not** write a seminar paper in the framework of this course.