KaKaRaKe - User-Friendly Visualization for Multiobjective Optimization with High-Dimensional Objective Vectors
Main Authors
Format
Conferences
Conference paper
Published
2020
Series
Subjects
Publication in research information system
Publisher
Dagstuhl Publishing
Original source
https://drops.dagstuhl.de/opus/volltexte/2020/12401/pdf/dagrep_v010_i001_p052_20031.pdf
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202007145314Käytä tätä linkitykseen.
Review status
Non-peer reviewed
ISSN
2192-5283
Conference
Dagstuhl Seminar
Language
English
Published in
Dagstuhl Reports
Is part of publication
Scalability in Multiobjective Optimization (Dagstuhl Seminar 20031)
Citation
- 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
License
Copyright© Kerstin Dächert, Kathrin Klamroth, Kaisa Miettinen, and Ralph E. Steuer