Content, progress and pedagogy of the
- Knowledge of formulating a linear optimization problem using
- Knowledge of important algorithms such as Dijkstras shortest
paths algorithm and the simplex method.
- Knowledge of the characteristics of 1-2 major metaheuristics
and the concept of a heuristic.
- Knowledge of general scheduling and routing problems.
- Is able to critically evaluate advantages of different models
and methods applied to a given problem.
- Can use different tools to solve realistic problems.
- Can formulate a real-life optimization problem with a
mathematical programming model.
- Apply scheduling and routing models to optimize automated
manufacturing and transportation / logistics systems and their
operational execution to achieve desired targets for productivity,
process quality etc.
- Must be able to rationalize and scientifically justify the use
of a specific solution method.
- Is able to recognize the value and limitations of a solution
- Should be able to communicate with experts the themes related
to mathematical programming
- Should be able to develop a model for a realistic problem and
to implement a solution method for the problem using the tools from
- Should be able to judge the applicability of the different
mathematical programming models and corresponding methods.
Type of instruction
The teaching is organized in accordance with the general form of
teaching. Please see the programme cirruculum §17.
Extent and expected workload
Since it is a 5 ECTS course module the expected workload is
150 hours for the student.
|Name of exam||Optimization, Scheduling and Routing|
|Type of exam|
Written or oral exam
|Assessment||7-point grading scale|
|Type of grading||Internal examination|
|Criteria of assessment||The criteria of assessment are stated in the Examination
Policies and Procedures|