B3 Non-refereed conference proceedings
KaKaRaKe - User-Friendly Visualization for Multiobjective Optimization with High-Dimensional Objective Vectors (2020)


Dächert, K., Klamroth, K., Miettinen, K., & Steuer, R. E. (2020). KaKaRaKe - User-Friendly Visualization for Multiobjective Optimization with High-Dimensional Objective Vectors. In C. M. Fonseca, K. Klamroth, G. Rudolph, & M. M. Wiecek (Eds.), Scalability in Multiobjective Optimization (Dagstuhl Seminar 20031) (10, pp. 97-103). Dagstuhl Publishing. Dagstuhl Reports. https://drops.dagstuhl.de/opus/volltexte/2020/12401/pdf/dagrep_v010_i001_p052_20031.pdf


JYU authors or editors


Publication details

All authors or editors: Dächert, Kerstin; Klamroth, Kathrin; Miettinen, Kaisa; Steuer, Ralph E.

Parent publication: Scalability in Multiobjective Optimization (Dagstuhl Seminar 20031)

Parent publication editors: Fonseca, Carlos M.; Klamroth, Kathrin; Rudolph, Günter; Wiecek, Margaret M.

Journal or series: Dagstuhl Reports

eISSN: 2192-5283

Publication year: 2020

Volume: 10

Issue number: 1

Pages range: 97-103

Publisher: Dagstuhl Publishing

Publication country: Germany

Publication language: English

Persistent website address: https://drops.dagstuhl.de/opus/volltexte/2020/12401/pdf/dagrep_v010_i001_p052_20031.pdf

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/71152


Keywords: multivariable methods; decision making; decision support systems; visualisation


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2020


Last updated on 2021-07-07 at 21:33