TIES5830 Datapohjainen optimointi ja päätöksenteko (5 op)

Students will learn the basics of online and offline data-driven multiobjective optimization, data preprocessing, various types of surrogate model selection, model management techniques, interactive data-driven optimization, and decision support tools.

Completion methods

Course assignments, active participation in lectures and discussions, group discussion, and final project

Assessment details

Assignments, active participation in lectures and discussions, final project. This may vary based on how the course is implemented.

Depends on the topics covered in the course (see the description of contents below).

Programming skills (preferably Python but not mandatory), basics of optimization (recommended) and machine learning, numerical methods. Completing the courses TIES598 (Nonlinear Multiobjective Optimization) and TIES451 (Selected Topics in Soft Computing) is beneficial.