A4 Artikkeli konferenssijulkaisussa
Artificial Decision Maker Driven by PSO : An Approach for Testing Reference Point Based Interactive Methods (2018)

Barba-González, C., Ojalehto, V., García-Nieto, J., Nebro, A. J., Miettinen, K., & Aldana-Montes, J. F. (2018). Artificial Decision Maker Driven by PSO : An Approach for Testing Reference Point Based Interactive Methods. In A. Auger, C. M. Fonseca, N. Lourenço, P. Machado, L. Paquete, & D. Whitley (Eds.), Parallel Problem Solving from Nature - PPSN XV : 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part 1 (pp. 274-285). Springer International Publishing. Lecture Notes in Computer Science, 11101. https://doi.org/10.1007/978-3-319-99253-2_22

JYU-tekijät tai -toimittajat

Julkaisun tiedot

Julkaisun kaikki tekijät tai toimittajat: Barba-González, Cristóbal; Ojalehto, Vesa; García-Nieto, José; Nebro, Antonio J.; Miettinen, Kaisa; Aldana-Montes, José F.

Emojulkaisu: Parallel Problem Solving from Nature - PPSN XV : 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part 1

Emojulkaisun toimittajat: Auger, Anne; Fonseca, Carlos M.; Lourenço, Nuno; Machado, Penousal; Paquete, Luís; Whitley, Darrell

ISBN: 978-3-319-99252-5

Lehti tai sarja: Lecture Notes in Computer Science

ISSN: 0302-9743

eISSN: 1611-3349

Julkaisuvuosi: 2018

Sarjan numero: 11101

Artikkelin sivunumerot: 274-285

Kustantaja: Springer International Publishing

Kustannuspaikka: Cham

Julkaisumaa: Sveitsi

Julkaisun kieli: englanti

DOI: https://doi.org/10.1007/978-3-319-99253-2_22

Julkaisun avoin saatavuus: Ei avoin

Julkaisukanavan avoin saatavuus: 

Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/59501

Tiivistelmä

Over the years, many interactive multiobjective optimization methods based on a reference point have been proposed. With a reference point, the decision maker indicates desirable objective function values to iteratively direct the solution process. However, when analyzing the performance of these methods, a critical issue is how to systematically involve decision makers. A recent approach to this problem is to replace a decision maker with an artificial one to be able to systematically evaluate and compare reference point based interactive methods in controlled experiments. In this study, a new artificial decision maker is proposed, which reuses the dynamics of particle swarm optimization for guiding the generation of consecutive reference points, hence, replacing the decision maker in preference articulation. We use the artificial decision maker to compare interactive methods. We demonstrate the artificial decision maker using the DTLZ benchmark problems with 3, 5 and 7 objectives to compare R-NSGA-II and WASF-GA as interactive methods. The experimental results show that the proposed artificial decision maker is useful and efficient. It offers an intuitive and flexible mechanism to capture the current context when testing interactive methods for decision making.

YSO-asiasanat: monitavoiteoptimointi; päätöksenteko; optimointi

Vapaat asiasanat: multiobjective optimization; preference articulation; multiple criteria decision making; particle swarm optimization

Liittyvät organisaatiot

Hankkeet, joissa julkaisu on tehty

OKM-raportointi: Kyllä

VIRTA-lähetysvuosi: 2018

JUFO-taso: 1