Where academic tradition
meets the exciting future

Turku Optimization Group (TOpGroup)

The mathematical and computational tools in optimization are used more frequently these days, as they provide efficient tools with negligible costs for many industries in the race for greater profits and better efficiency. The optimization group does research in both modeling and implementation of practical problems from industry and further development of algorithms. The following areas of optimization are at focus:

Research Unit Web Page: http://www.math.utu.fi/en/research/groups/opt/

Leader of the unit

Marko M. Mäkelä

Senior Researchers

Yury Nikulin Napsu Karmitsa Stefan Emet


Kiril Kuzmin

Doctoral Students

Seppo Pulkkinen Napsu Karmitsa Stefan Emet


3D Packing Problem

With Kine Robot Solutions Oy

Large Scale Mixed Integer Global Optimization

With Åbo Akademi University

Modeling the Ferry Services of the Archipelago

With the Centre for Maritime Studies


Click here to see the full list of publications from the TUCS Publication Database

The latest updated publications:

Vladimir Emelichev, Yury Nikulin, T-1 Stability Measures for Multicriteria Quadratic Integer Programming Problem of Finding Extremum Solutions. TUCS Technical Reports 1194, TUCS, 2018.

Napsu Karmitsa, Sona Taheri, Adil Bagirov, Pauliina Mäkinen, Clusterwise Linear Regression Based Missing Value Imputation of Data Preprocessing. TUCS Technical Reports 1193, 2018.

Alaleh Maskooki, Yury Nikulin, Multiobjective Efficient Routing In a Dynamic Network. TUCS Technical Reports 1198, TUCS, 2018.

Vladimir Emelichev, Yury Nikulin, Vladimir Korotkov, Stability Analysis of Efficient Portfolios in a Discrete Variant of Multicriteria Investment Problem with Savage’s Risk Criteria. Computer Science Journal of Moldova 25(3 (75)), 303–328, 2017.

Outi Wilppu, Marko M. Mäkelä, Yury Nikulin, New Two-Slope Parameterized Achievement Scalarizing Functions for Nonlinear Multiobjective Optimization. In: Nicholas J. Daras, Themistocles M. Rassias (Eds.), Operations Research, Engineering, and Cyber Security, Optimization and Its Applications 113, 403–422, Springer, 2017.

Sepinoud Azimi, Joonas Jalonen, Jarkko Kari, Ion Petre (Eds.), Computability in Europe 2017, TUCS General Publication, 2017.

Noora Nieminen, Garbling Schemes and Applications. TUCS Dissertations 219. 2017.

Vladimir Emelichev, Yury Nikulin, Aspects of Stability for Multicriteria Quadratic Problems of Boolean Programming. TUCS Technical Reports 1188, TUCS, 2017.

Vladimir Emelichev, Yury Nikulin, Stability of Extremum Solutions in Vector Quadratic Discrete Optimization. TUCS Technical Reports 1189, TUCS, 2017.

Ville-Pekka Eronen, Jan Kronqvist, Tapio Westerlund, Marko M. Mäkelä, Napsu Karmitsa, Extended Supporting Hyperplane Algorithm for Generalized Convex Nonsmooth MINLP Problems. TUCS Technical Reports 1179, TUCS, 2017.

Kaisa Joki, Adil M. Bagirov, Napsu Karmitsa, Marko M. Mäkelä, Sona Taheri, Double Bundle Method for Nonsmooth DC Optimization. TUCS Technical Reports 1173, TUCS, 2017.

Kaisa Joki, Adil M. Bagirov, Napsu Karmitsa, Marko M. Mäkelä, Sona Taheri, New Bundle Method for Clusterwise Linear Regression Utilizing Support Vector Machines. TUCS Technical Reports 1190, TUCS, 2017.

Napsu Karmitsa, Manlio Gaudioso, Kaisa Joki, Splitting Metrics Diagonal Bundle Method for Large-Scale Nonconvex Nonsmooth Optimization. TUCS Technical Reports 1178, TUCS, 2017.

Outi Montonen, Kaisa Joki, Multiobjective Double Bundle Method for Nonsmooth Constrained Multiobjective DC Optimization. TUCS Technical Reports 1174, TUCS, 2017.

Tapio Westerlund, Ville-Pekka Eronen, Marko M. Mäkelä, Using Supporting Hyperplane Techniques in Solving Generalized Convex MINLP Problems. TUCS Technical Reports 1186, TUCS, 2017.