TIES598 Nonlinear Multiobjective Optimization (5 cr)

Study level:
Advanced studies
Grading scale:
English, Finnish
Responsible organisation:
Faculty of Information Technology
Curriculum periods:
2020-2021, 2021-2022, 2022-2023



Optimization is needed in different application fields and typically there are several conflicting objectives to be optimized simultaneously. Multiobjective optimization methods are then needed to support the decision maker in finding the best compromise solution.
TIES598 Nonlinear multiobjective optimization is a master level course in mathematical information technology ( tietotekniikka in Finnish) where the emphasis is on solving nonlinear multiobjective optimization problems. The course is compulsory in the thematic module on decision analytics and it is suitable e.g. as an optional course of the MSc in computational sciences. The course deals with topics ranging from theory to various optimization methods and software. In addition, there will be examples of solving practical optimization problems and what kind of challenges they pose. The course takes the students to the edge of the current knowledge in multiobjective optimization and, during the course, students will familiarize themselves with novel methods proposed in recent scientific publications. In addition, visualization of solutions and various applications of data driven decision support are considered.

Completion methods

The course does not include an exam, but the students are graded based on the assignments and their active participation in lectures and group discussions.

Learning outcomes

Recognize multiobjective optimization problems and skills to solve them. Understand why multiobjective optimization methods are needed. Understand the significance of decision support. Understand basic concepts in solving multiobjective optimization problems. Understand optimality in multiobjective optimization. Understand different approaches to solve multiobjective optimization problems. Understand basics of choosing an appropriate method and implementing multiobjective optimization methods. Know how to find and apply software for solving multiobjective optimization problems.

Description of prerequisites

Basic knowledge about single objective optimization, numerical methods and computer programming. Previous completion of the courses TIEA382 Linear and discrete optimization is recommended and TIES483 Nonlinear optimization is expected.


  • Miettinen, K., 1999, Nonlinear Multiobjective Optimization, Kluwer Academic Publishers; ISBN: 0-7923-8278-1

Completion methods

Method 1

Select all marked parts
Parts of the completion methods

Teaching (5 cr)

Participation in teaching
Grading scale:
English, Finnish