After successful completion of the course, students are able to

• use selected methods of model-based decision support
• assess the potential applications of model-based decision support in organizations
• Computer-aided planning and optimization of business processes
• outline complexity of mathematical programming and assess the usefulness of heuristic optimization methods

Decision analysis, model-based decision support with focus on mathematical models; modelling process; simulation versus mathematical models, optimisation models; measuring productivity and efficiency (Data Envelopment Analysis); waiting line models; network planning and graph theory models; inter-temporal optimisation; modelling languages (GAMS).

Inverted classroom, podcasts, video, discusion in online and/or face-to-face meetings, home assignments, tests

Information meeting on Thu March 7, 2024, 11:30 a.m., venue: Sem 127

Home assignments and  tests. Your presence at the meetings is recommended but not necessary.

It is recommended that students calculate with matrices, discuss elementary functions, apply Bayes' theorem, explain conditional probabilities, experiment with algorithms, and work on and use programming codes.