Learning Outcomes
The course presents the theoretical basics and practical applications of stochastic methods of operations research. The specific objective for the students is to understand the basic concepts of stochastic processes - Markov chains and queuing theory and to be able to apply them for solving relevant problems.
Course Content (Syllabus)
Stochastic processes and discrete-time Markov chains: classification of states, long-run properties. Markovian processes with rewards, control and otimization. Applications in inventory control and maintenance management.
Continuous-time Markov chains, birth-and-death processes.
Queuing theory: classes and examples of queuing phenomena. Markovian queuing models with a single or multiple servers, finite or infinite queue, finite or infinite population. Priority in service queues. Queuing networks. Optimisation of queuing systems.
Description
The final grade M is a combination of the grades in the final written examination (T), the midterm examination (Π) and the project/homework (E) as follows:
• If either Τ < 4,5 or (Τ+Π)/2 < 4, then the final grade is Μ = (0,8)Τ.
• In every other case the final grade is Μ = max {(0,6)Τ + (0,3)Π + (0,2)Ε, (0,8)T}.