No upcoming implementations. See the syllabus for more information.
Learning outcomes of the course
The students know the concepts and methods of optimization and simulation. They are able to formulate a working-life problem as an optimization task or a simulation study and solve the problem using a computer.
EUR-ACE Knowledge and Understanding: Students must know and understand the mathematical principles, concepts and methods underlying logistics.
EUR-ACE Engineering Analysis: Students must have the ability to identify, formulate and solve engineering problems using mathematical methods.
TELNA: Students are able to use mathematics in a technical environment.
Linear and non-linear optimization, elements of graph theory, optimization in networks, simulation studies, elements of queuing theory, input and output data analysis. The use of Excel, Mathcad and other computer programs for optimization and simulation.
Prerequisites and co-requisites
The students know probability distributions and can work with computer programs Excel and Mathcad
Assessment criteria - grade 1 and 2
Sufficient (1): Student has gained knowledge of course objectives but face challenges to utilize them in practice.
Satisfactory (2): Student has gained knowledge of course objectives and can utilize them partly in practice.
Assessment criteria - grade 3 and 4
Good (3): Student has gained understanding of course objectives and can utilize them in practice.
Very good (4): Student has attained very good level of course objectives and can apply them into practice.
Assessment criteria - grade 5
Excellent (5): Student has attained an excellent level of course objectives and can apply them into practice in innovative manner.