A4 Article in conference proceedings
A Systematic Way of Structuring Real-World Multiobjective Optimization Problems (2023)

Afsar, B., Silvennoinen, J., & Miettinen, K. (2023). A Systematic Way of Structuring Real-World Multiobjective Optimization Problems. In M. Emmerich, A. Deutz, H. Wang, A. V. Kononova, B. Naujoks, K. Li, K. Miettinen, & I. Yevseyeva (Eds.), Evolutionary Multi-Criterion Optimization : 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20–24, 2023, Proceedings (pp. 593-605). Springer Nature Switzerland. Lecture Notes in Computer Science, 13970. https://doi.org/10.1007/978-3-031-27250-9_42

JYU authors or editors

Publication details

All authors or editors: Afsar, Bekir; Silvennoinen, Johanna; Miettinen, Kaisa

Parent publication: Evolutionary Multi-Criterion Optimization : 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20–24, 2023, Proceedings

Parent publication editors: Emmerich, Michael; Deutz, André; Wang, Hao; Kononova, Anna V.; Naujoks, Boris; Li, Ke; Miettinen, Kaisa; Yevseyeva, Iryna

Place and date of conference: Leiden, The Netherlands, 20.-24.3.2023

ISBN: 978-3-031-27249-3

eISBN: 978-3-031-27250-9

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

eISSN: 1611-3349

Publication year: 2023

Publication date: 21/02/2023

Number in series: 13970

Pages range: 593-605

Number of pages in the book: 636

Publisher: Springer Nature Switzerland

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-031-27250-9_42

Publication open access: Not open

Publication channel open access:

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/86186


In recent decades, the benefits of applying multiobjective optimization (MOO) methods in real-world applications have rapidly increased. The MOO literature mostly focuses on problem-solving, typically assuming the problem has already been correctly formulated. The necessity of verifying the MOO problem and the potential impacts of having an incorrect problem formulation on the optimization results are not emphasized enough in the literature. However, verification is crucial since the optimization results will not be meaningful without an accurate problem formulation, not to mention the resources spent in the optimization process being wasted.

In this paper, we focus on the MOO problem structuring, which we believe deserves more attention. The novel contribution is the proposed systematic way of structuring MOO problems that leverages problem structuring approaches from the literature on multiple criteria decision analysis (MCDA). They are not directly applicable to the formulation of MOO problems since the objective functions in the MOO problem depend on decision variables and constraint functions, whereas MCDA problems have a given set of solution alternatives characterized by criterion values. Therefore, we propose to elicit expert knowledge to identify decision variables and constraint functions, in addition to the objective functions, to construct a MOO problem appropriately. Our approach also enables the verification and validation of the problem before the actual decision making process.

Keywords: multi-objective optimisation; applications (applying); decision making; problem solving; stakeholder groups

Free keywords: problem structuring; MOO problem formulation; eliciting expert knowledge; identifying objectives; decision making; stakeholder interviews

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2023

Preliminary JUFO rating: 1

Last updated on 2023-03-04 at 08:40