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 toimittajatBarba-González, Cristóbal; Ojalehto, Vesa; García-Nieto, José; Nebro, Antonio J.; Miettinen, Kaisa; Aldana-Montes, José F.

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

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

ISBN978-3-319-99252-5

Lehti tai sarjaLecture Notes in Computer Science

ISSN0302-9743

eISSN1611-3349

Julkaisuvuosi2018

Sarjan numero11101

Artikkelin sivunumerot274-285

KustantajaSpringer International Publishing

KustannuspaikkaCham

JulkaisumaaSveitsi

Julkaisun kielienglanti

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

Julkaisun avoin saatavuusEi 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-asiasanatmonitavoiteoptimointipäätöksentekooptimointi

Vapaat asiasanatmultiobjective optimization; preference articulation; multiple criteria decision making; particle swarm optimization


Liittyvät organisaatiot

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Hankkeet, joissa julkaisu on tehty


OKM-raportointiKyllä

Raportointivuosi2018

JUFO-taso1


Viimeisin päivitys 2023-03-10 klo 12:30