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.