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Recent news

Risto Heikkinen was awarded the best poster award at the INFORMS 2024 Advances in Decision Analysis conference, being held at Aalto University

Bhupinder Singh Saini won The MCDM Doctoral Dissertation Award 2024

Giovanni Misitano won the second prize in Millennium Graduate Student Contest!See the full story here

We have new Master thesis topics! You can check them Here! (updated November 2023)

We have a new group name now! Welcome to Multiobjective Optimization Group

Kaisa Miettinen has received the Georg Cantor Award of the International Society on Multiple Criteria Decision Making

Profiling action of the university "Decision Analytics utilizing Causal Models and Multiobjective Optimization (DEMO)" has received funding from the Academy of Finland

In 2015-2017 we had a FiDiPro professor at The Multiobjective optimization group

Multiobjective Optimization Group

Faculty of Information Technology

University of Jyväskylä, Finland



The Multiobjective optimization group of the University of Jyväskylä, Finland, is a part of the Faculty of Information Technology and is headed by Prof. Kaisa Miettinen (since 1998). The research interests of the group are focused on (nonlinear) multiobjective optimization in the presence of conflicting objectives, including e.g.

  • method development, with focus on
    • interactive methods
    • evolutionary and hybrid methods
  • theoretical aspects
  • software development
  • real-world applications
    • simulation-based problems
    • data-driven problems (prescriptive analytics)
Overall, the work is inspired by real-life applications with the interest of supporting decision making. Interactive multiobjective optimization methods are at the very core of the interests of the group.

The Multiobjective Optimization Group is one of the few groups that specializes in implementing interactive methods, in particular, as open access software. A DESDEO framework is under preparation.

Besides simulation-based optimization, the group is interested in data-driven decision support and in particular prescriptive analytics whch we call decision analytics when multiple conflicting objectives are considered in making recommendations as decisions based on data available. We are active in the new thematic research field of JYU: Decision Analytics unitizing Causal Models and Multiobjective Optimization (DEMO) (with Kaisa Miettinen as the director). We are also interested in employing artificial intelligence and machine learning and, in particular, explainable artificial intelligence.

In the group, in the general theoretical and methodological development, the focus is typically on methods which are suitable and applicable in the case of industrial applications. Even though the methods applied are typically based on strong mathematical foundations, in practice, the applications may lack nice mathematical structures (they can be e.g. black box models and computationally expensive) and these practical characteristics must be taken into account when developing methods. Another characteristic of the methods developed is application-independence. In other words, behind the application-specific user-interface, the optimization method can be the same for designing paper machines or planning radiotherapy treatment.

Among others, the industrial applications considered deal with improvement of product properties, making production processes and their controls more efficient, or finding the best shape or structure etc.