Simulation and Optimization Modeling, Graph Models


The aim of the course is to introduce students to discrete and continuous event simulation, optimization and network analysis by means of applied examples in concrete business situations. After the course, students will be able to translate business problems into mathematical models that are easily solvable with software and interpret back the solution into a business decision.


Course structure:

Lecture 40%, Hands-on practice 60%


Learning Objectives:

  • Overview of simulation methods for different business problems.
  • Introduction to optimization theory with practical examples.
  • Overview of graph theory by real-life use cases.


Learning outcomes:

At the end of this course, the student should be able to:

  • Identify situations where they can use different optimization methods.
  • Recognize the difference between discrete and continuous event simulation.
  • Formulate a business situation as a mathematical problem, and state the assumptions and limitations of the solution.
  • Apply different criteria to detect communities and outliers in networks.


Language: English