On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems
J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 356–359.
Download
No fulltext has been uploaded.
Conference Paper
| English
Author
Rook, Jeroen;
Trautmann, Heike;
Bossek, JakobLibreCat 
;
Grimme, Christian
;
Grimme, ChristianDepartment
Abstract
Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.
Publishing Year
Proceedings Title
Proceedings of the Genetic and Evolutionary Computation Conference Companion
forms.conference.field.series_title_volume.label
GECCO’22
Page
356–359
ISBN
LibreCat-ID
Cite this
Rook J, Trautmann H, Bossek J, Grimme C. On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO’22. Association for Computing Machinery; 2022:356–359. doi:10.1145/3520304.3528998
Rook, J., Trautmann, H., Bossek, J., & Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359. https://doi.org/10.1145/3520304.3528998
@inproceedings{Rook_Trautmann_Bossek_Grimme_2022, place={New York, NY, USA}, series={GECCO’22}, title={On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems}, DOI={10.1145/3520304.3528998}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion}, publisher={Association for Computing Machinery}, author={Rook, Jeroen and Trautmann, Heike and Bossek, Jakob and Grimme, Christian}, year={2022}, pages={356–359}, collection={GECCO’22} }
Rook, Jeroen, Heike Trautmann, Jakob Bossek, and Christian Grimme. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3520304.3528998.
J. Rook, H. Trautmann, J. Bossek, and C. Grimme, “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, pp. 356–359, doi: 10.1145/3520304.3528998.
Rook, Jeroen, et al. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, 2022, pp. 356–359, doi:10.1145/3520304.3528998.
Google Scholar
ISBN Search