Upon successful completion of the course, the students should
- have acquired the mentality and language of optimization
- know how to recognize, model and formulate real engineering problems as optimization problems
- understand the underlying theory, concepts and properties related to each of the optimization tools, especially those that are useful for computing solutions efficiently
- be able to design, implement and simulate practical algorithms to solve the various optimization problems
- be able to analyze the structures of problems and associated solutions, as well as the relationships between different problems
The evaluation will consist of two parts:
a) Portfolio (25 %), where some of the exercises will be mini-projects. Information about the portfolio will be given in Fronter at the startup of the course.
b) Final written exam 3 hours (75 %). Graded assessment.
Faculty of Engineering and Science