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