Informaatioteknologian tiedekunta

Hakanen Jussi, Yliopistotutkija / Senior Researcher

Viimeisin muutos tiistai 28. helmikuuta 2017, 15.04
Teollinen optimointi, Laskennalliset tieteet, Sovellettu matematiikka / Industrial Optimization
+358 40 805 3260
AgC 426.3

Member of Industrial Optimization Group

I am a principal investigator in the FINNOPT project funded by Tekes the Finnish Funding Agency for Innovation.

Lectured courses:

Research interests

Multiobjective optimization: industrial applications, methods, especially interactive methods, theory of multiobjective optimization

My main research interest is multiobjective optimization. Especially, I am interested in industrial applications of multiobjective optimization and that was also the topic of my doctoral thesis. Industrial problems are usually computationally challenging and there are several conflicting performance criteria that need to be considered simultaneously. Therefore, it is very important to have efficient optimization methods in industrial process design. When considering multiple conflicting criteria there is no unique optimal solution of the optimization problem, but instead a set of mathematically equal compromise solutions, that are often called Pareto optimal solutions. Selection of the final solution among equally good compromise solutions requires some additional information about the problem in question. The specialist who is able to evaluate and compare these mathematically equivalent solutions is called a decision maker. Interactive multiobjective optimization methods are computationally efficient (in the sense of compromise solutions computed during the solution process) and their solution procedure utilizes the preferences of the decision maker continuously during the interactive solution procedure which makes them well suited for industrial applications.

Single objective optimization: sensitivity analysis, efficient optimizers for complex problems

An important research area related to multiobjective optimization is single objective optimization. Many multiobjective optimization methods utilize single objective optimization within the multiobjective optimization algorithm. Thus, efficient single objective optimizers for computationally demanding problems can greatly improve the overall performance of the multiobjective optimization methods.


My list of publications (pdf)