{"author":[{"first_name":"J","full_name":"Rook, J","last_name":"Rook"},{"first_name":"Heike","full_name":"Trautmann, Heike","id":"100740","last_name":"Trautmann","orcid":"0000-0002-9788-8282"},{"first_name":"Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","full_name":"Bossek, Jakob","id":"102979"},{"first_name":"C","full_name":"Grimme, C","last_name":"Grimme"}],"date_updated":"2026-02-19T15:12:35Z","doi":"10.1145/3520304.3528998","publication_identifier":{"isbn":["9781450392686"]},"page":"356–359","citation":{"ieee":"J. Rook, H. Trautmann, J. Bossek, and C. Grimme, “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 2022, pp. 356–359, doi: <a href=\"https://doi.org/10.1145/3520304.3528998\">10.1145/3520304.3528998</a>.","chicago":"Rook, J, Heike Trautmann, Jakob Bossek, and C Grimme. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, edited by J Fieldsend and M. Wagner, 356–359. GECCO ’22. New York, NY, USA: Association for Computing Machinery, 2022. <a href=\"https://doi.org/10.1145/3520304.3528998\">https://doi.org/10.1145/3520304.3528998</a>.","ama":"Rook J, Trautmann H, Bossek J, Grimme C. On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In: Fieldsend J, Wagner M, eds. <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>. GECCO ’22. Association for Computing Machinery; 2022:356–359. doi:<a href=\"https://doi.org/10.1145/3520304.3528998\">10.1145/3520304.3528998</a>","apa":"Rook, J., Trautmann, H., Bossek, J., &#38; Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In J. Fieldsend &#38; M. Wagner (Eds.), <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i> (pp. 356–359). Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3520304.3528998\">https://doi.org/10.1145/3520304.3528998</a>","short":"J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: J. Fieldsend, M. Wagner (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 356–359.","bibtex":"@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={<a href=\"https://doi.org/10.1145/3520304.3528998\">10.1145/3520304.3528998</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion}, publisher={Association for Computing Machinery}, author={Rook, J and Trautmann, Heike and Bossek, Jakob and Grimme, C}, editor={Fieldsend, J and Wagner, M.}, year={2022}, pages={356–359}, collection={GECCO ’22} }","mla":"Rook, J., et al. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, edited by J Fieldsend and M. Wagner, Association for Computing Machinery, 2022, pp. 356–359, doi:<a href=\"https://doi.org/10.1145/3520304.3528998\">10.1145/3520304.3528998</a>."},"place":"New York, NY, USA","department":[{"_id":"34"},{"_id":"819"}],"user_id":"14972","series_title":"GECCO ’22","_id":"46305","type":"conference","status":"public","editor":[{"first_name":"J","last_name":"Fieldsend","full_name":"Fieldsend, J"},{"full_name":"Wagner, M.","last_name":"Wagner","first_name":"M."}],"date_created":"2023-08-04T07:14:24Z","publisher":"Association for Computing Machinery","title":"On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems","year":"2022","language":[{"iso":"eng"}],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","abstract":[{"lang":"eng","text":"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."}]}