A4 Article in conference proceedings
A feature rich distance-based many-objective visualisable test problem generator (2019)


Fieldsend, J., Chugh, T., Allmendinger, R., & Miettinen, K. (2019). A feature rich distance-based many-objective visualisable test problem generator. In GECCO '19 : Proceedings of the Genetic and Evolutionary Computation Conference (pp. 541-549). New York: ACM. doi:10.1145/3321707.3321727


JYU authors or editors


Publication details

All authors or editors: Fieldsend, Jonathan; Chugh, Tinkle; Allmendinger, Richard; Miettinen, Kaisa

Parent publication: GECCO '19 : Proceedings of the Genetic and Evolutionary Computation Conference

ISBN: 978-1-4503-6111-8

Publication year: 2019

Pages range: 541-549

Number of pages in the book: 1545

Publisher: ACM

Place of Publication: New York

Publication country: United States

Publication language: English

DOI: http://doi.org/10.1145/3321707.3321727

Open Access: Publication channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/65086

Additional information: GECCO '19 : Genetic and Evolutionary Computation Conference. Prague, Czech Republic — July 13-17, 2019.


Keywords: multi-objective optimisation; evolutionary computation; visualisation; benchmarking

Free keywords: multi-objective test problems; evolutionary optimisation; test suite


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1


Last updated on 2020-18-10 at 21:26