A4 Article in conference proceedings
IRA-EMO : Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization (2019)

Saborido, R., Ruiz, A. B., Luque, M., & Miettinen, K. (2019). IRA-EMO : Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization. In K. Deb, E. Goodman, C. A. C. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings (pp. 618-630). Springer International Publishing. Lecture Notes in Computer Science, 11411. https://doi.org/10.1007/978-3-030-12598-1_49

JYU authors or editors

Publication details

All authors or editors: Saborido, Rubén; Ruiz, Ana B.; Luque, Mariano; Miettinen, Kaisa

Parent publication: Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings

Parent publication editors: Deb, Kalyanmoy; Goodman, Erik; Coello, Carlos A. Coello; Klamroth, Kathrin; Miettinen, Kaisa; Mostaghim, Sanaz; Reed, Patrick

ISBN: 978-3-030-12597-4

Journal or series: Lecture Notes in Computer Science

ISSN: 0302-9743

eISSN: 1611-3349

Publication year: 2019

Number in series: 11411

Pages range: 618-630

Number of pages in the book: 757

Publisher: Springer International Publishing

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-030-12598-1_49

Publication open access: Not open

Publication channel open access: 

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/63115

Abstract

We propose a new interactive evolutionary multiobjective optimization method, IRA-EMO. At each iteration, the decision maker (DM) expresses her/his preferences as an interesting interval for objective function values. The DM also specifies the number of representative Pareto optimal solutions in these intervals referred to as regions of interest one wants to study. Finally, a real-life engineering three-objective optimization problem is used to demonstrate how IRA-EMO works in practice for finding the most preferred solution.

Keywords: multi-objective optimisation; preferences

Free keywords: evolutionary multi-objective optimization; reference point; region of interest; interactive methods

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Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1