[{"publication":"Parallel Problem Solving from Nature — PPSN XVII","type":"conference","status":"public","editor":[{"full_name":"Rudolph, Günter","last_name":"Rudolph","first_name":"Günter"},{"first_name":"Anna V.","last_name":"Kononova","full_name":"Kononova, Anna V."},{"first_name":"Hernán","full_name":"Aguirre, Hernán","last_name":"Aguirre"},{"full_name":"Kerschke, Pascal","last_name":"Kerschke","first_name":"Pascal"},{"last_name":"Ochoa","full_name":"Ochoa, Gabriela","first_name":"Gabriela"},{"first_name":"Tea","last_name":"Tušar","full_name":"Tušar, Tea"}],"abstract":[{"lang":"eng","text":"Hyperparameter optimization (HPO) is a key component of machine learning models for achieving peak predictive performance. While numerous methods and algorithms for HPO have been proposed over the last years, little progress has been made in illuminating and examining the actual structure of these black-box optimization problems. Exploratory landscape analysis (ELA) subsumes a set of techniques that can be used to gain knowledge about properties of unknown optimization problems. In this paper, we evaluate the performance of five different black-box optimizers on 30 HPO problems, which consist of two-, three- and five-dimensional continuous search spaces of the XGBoost learner trained on 10 different data sets. This is contrasted with the performance of the same optimizers evaluated on 360 problem instances from the black-box optimization benchmark (BBOB). We then compute ELA features on the HPO and BBOB problems and examine similarities and differences. A cluster analysis of the HPO and BBOB problems in ELA feature space allows us to identify how the HPO problems compare to the BBOB problems on a structural meta-level. We identify a subset of BBOB problems that are close to the HPO problems in ELA feature space and show that optimizer performance is comparably similar on these two sets of benchmark problems. We highlight open challenges of ELA for HPO and discuss potential directions of future research and applications."}],"department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504","_id":"46306","language":[{"iso":"eng"}],"publication_identifier":{"isbn":["978-3-031-14714-2"]},"page":"575–589","citation":{"ama":"Schneider L, Schäpermeier L, Prager RP, Bischl B, Trautmann H, Kerschke P. HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tušar T, eds. <i>Parallel Problem Solving from Nature — PPSN XVII</i>. Springer International Publishing; 2022:575–589. doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">10.1007/978-3-031-14714-2_40</a>","chicago":"Schneider, Lennart, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, and Pascal Kerschke. “HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.” In <i>Parallel Problem Solving from Nature — PPSN XVII</i>, edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tušar, 575–589. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">https://doi.org/10.1007/978-3-031-14714-2_40</a>.","ieee":"L. Schneider, L. Schäpermeier, R. P. Prager, B. Bischl, H. Trautmann, and P. Kerschke, “HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis,” in <i>Parallel Problem Solving from Nature — PPSN XVII</i>, 2022, pp. 575–589, doi: <a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">10.1007/978-3-031-14714-2_40</a>.","apa":"Schneider, L., Schäpermeier, L., Prager, R. P., Bischl, B., Trautmann, H., &#38; Kerschke, P. (2022). HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tušar (Eds.), <i>Parallel Problem Solving from Nature — PPSN XVII</i> (pp. 575–589). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">https://doi.org/10.1007/978-3-031-14714-2_40</a>","bibtex":"@inproceedings{Schneider_Schäpermeier_Prager_Bischl_Trautmann_Kerschke_2022, place={Cham}, title={HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">10.1007/978-3-031-14714-2_40</a>}, booktitle={Parallel Problem Solving from Nature — PPSN XVII}, publisher={Springer International Publishing}, author={Schneider, Lennart and Schäpermeier, Lennart and Prager, Raphael Patrick and Bischl, Bernd and Trautmann, Heike and Kerschke, Pascal}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tušar, Tea}, year={2022}, pages={575–589} }","mla":"Schneider, Lennart, et al. “HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis.” <i>Parallel Problem Solving from Nature — PPSN XVII</i>, edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 575–589, doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_40\">10.1007/978-3-031-14714-2_40</a>.","short":"L. Schneider, L. Schäpermeier, R.P. Prager, B. Bischl, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 575–589."},"place":"Cham","year":"2022","date_created":"2023-08-04T07:15:16Z","author":[{"first_name":"Lennart","last_name":"Schneider","full_name":"Schneider, Lennart"},{"first_name":"Lennart","full_name":"Schäpermeier, Lennart","last_name":"Schäpermeier"},{"first_name":"Raphael Patrick","last_name":"Prager","full_name":"Prager, Raphael Patrick"},{"first_name":"Bernd","last_name":"Bischl","full_name":"Bischl, Bernd"},{"id":"100740","full_name":"Trautmann, Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","first_name":"Heike"},{"first_name":"Pascal","last_name":"Kerschke","full_name":"Kerschke, Pascal"}],"date_updated":"2023-10-16T12:51:27Z","publisher":"Springer International Publishing","doi":"10.1007/978-3-031-14714-2_40","title":"HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis"},{"year":"2022","date_created":"2023-11-14T15:58:58Z","publisher":"Springer International Publishing","title":"BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems","publication":"Parallel Problem Solving from Nature (PPSN XVII)","abstract":[{"lang":"eng","text":"In multimodal multi-objective optimization (MMMOO), the focus is not solely on convergence in objective space, but rather also on explicitly ensuring diversity in decision space. We illustrate why commonly used diversity measures are not entirely appropriate for this task and propose a sophisticated basin-based evaluation (BBE) method. Also, BBE variants are developed, capturing the anytime behavior of algorithms. The set of BBE measures is tested by means of an algorithm configuration study. We show that these new measures also transfer properties of the well-established hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective space convergence. Moreover, we advance MMMOO research by providing insights into the multimodal performance of the considered algorithms. Specifically, algorithms exploiting local structures are shown to outperform classical evolutionary multi-objective optimizers regarding the BBE variants and respective trade-off with HV."}],"language":[{"iso":"eng"}],"keyword":["Anytime behavior","Benchmarking","Continuous optimization","Multi-objective optimization","Multimodality","Performance metric"],"publication_identifier":{"isbn":["978-3-031-14714-2"]},"page":"192–206","citation":{"short":"J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 192–206.","mla":"Heins, Jonathan, et al. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 192–206, doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">10.1007/978-3-031-14714-2_14</a>.","bibtex":"@inproceedings{Heins_Rook_Schäpermeier_Kerschke_Bossek_Trautmann_2022, place={Cham}, series={Lecture Notes in Computer Science}, title={BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">10.1007/978-3-031-14714-2_14</a>}, booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer International Publishing}, author={Heins, Jonathan and Rook, Jeroen and Schäpermeier, Lennart and Kerschke, Pascal and Bossek, Jakob and Trautmann, Heike}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tusar, Tea}, year={2022}, pages={192–206}, collection={Lecture Notes in Computer Science} }","apa":"Heins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J., &#38; Trautmann, H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tusar (Eds.), <i>Parallel Problem Solving from Nature (PPSN XVII)</i> (pp. 192–206). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">https://doi.org/10.1007/978-3-031-14714-2_14</a>","ama":"Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tusar T, eds. <i>Parallel Problem Solving from Nature (PPSN XVII)</i>. Lecture Notes in Computer Science. Springer International Publishing; 2022:192–206. doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">10.1007/978-3-031-14714-2_14</a>","chicago":"Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” In <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">https://doi.org/10.1007/978-3-031-14714-2_14</a>.","ieee":"J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, and H. Trautmann, “BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems,” in <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, 2022, pp. 192–206, doi: <a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">10.1007/978-3-031-14714-2_14</a>."},"place":"Cham","author":[{"last_name":"Heins","full_name":"Heins, Jonathan","first_name":"Jonathan"},{"first_name":"Jeroen","last_name":"Rook","full_name":"Rook, Jeroen"},{"first_name":"Lennart","full_name":"Schäpermeier, Lennart","last_name":"Schäpermeier"},{"first_name":"Pascal","full_name":"Kerschke, Pascal","last_name":"Kerschke"},{"id":"102979","full_name":"Bossek, Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","first_name":"Jakob"},{"first_name":"Heike","last_name":"Trautmann","full_name":"Trautmann, Heike"}],"date_updated":"2023-12-13T10:47:50Z","doi":"10.1007/978-3-031-14714-2_14","type":"conference","status":"public","editor":[{"first_name":"Günter","full_name":"Rudolph, Günter","last_name":"Rudolph"},{"first_name":"Anna V.","full_name":"Kononova, Anna V.","last_name":"Kononova"},{"full_name":"Aguirre, Hernán","last_name":"Aguirre","first_name":"Hernán"},{"first_name":"Pascal","last_name":"Kerschke","full_name":"Kerschke, Pascal"},{"last_name":"Ochoa","full_name":"Ochoa, Gabriela","first_name":"Gabriela"},{"full_name":"Tusar, Tea","last_name":"Tusar","first_name":"Tea"}],"department":[{"_id":"819"}],"series_title":"Lecture Notes in Computer Science","user_id":"102979","_id":"48882","extern":"1"},{"abstract":[{"text":"Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of solutions (evolutionary diversity optimisation). In this study, we introduce a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component traveling thief problem. The results show the capability of the co-evolutionary algorithm to achieve significantly higher diversity compared to the baseline evolutionary diversity algorithms from the literature.","lang":"eng"}],"publication":"Parallel Problem Solving from Nature (PPSN XVII)","language":[{"iso":"eng"}],"keyword":["Co-evolutionary algorithms","Evolutionary diversity optimisation","Quality diversity","Traveling thief problem"],"year":"2022","title":"Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem","date_created":"2023-11-14T15:59:00Z","publisher":"Springer International Publishing","status":"public","editor":[{"first_name":"Günter","last_name":"Rudolph","full_name":"Rudolph, Günter"},{"first_name":"Anna V.","last_name":"Kononova","full_name":"Kononova, Anna V."},{"full_name":"Aguirre, Hernán","last_name":"Aguirre","first_name":"Hernán"},{"first_name":"Pascal","full_name":"Kerschke, Pascal","last_name":"Kerschke"},{"first_name":"Gabriela","last_name":"Ochoa","full_name":"Ochoa, Gabriela"},{"first_name":"Tea","last_name":"Tu\\v sar","full_name":"Tu\\v sar, Tea"}],"type":"conference","extern":"1","department":[{"_id":"819"}],"user_id":"102979","series_title":"Lecture Notes in Computer Science","_id":"48894","page":"237–249","citation":{"ama":"Nikfarjam A, Neumann A, Bossek J, Neumann F. Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tu\\v sar T, eds. <i>Parallel Problem Solving from Nature (PPSN XVII)</i>. Lecture Notes in Computer Science. Springer International Publishing; 2022:237–249. doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">10.1007/978-3-031-14714-2_17</a>","ieee":"A. Nikfarjam, A. Neumann, J. Bossek, and F. Neumann, “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem,” in <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, 2022, pp. 237–249, doi: <a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">10.1007/978-3-031-14714-2_17</a>.","chicago":"Nikfarjam, Adel, Aneta Neumann, Jakob Bossek, and Frank Neumann. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” In <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tu\\v sar, 237–249. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">https://doi.org/10.1007/978-3-031-14714-2_17</a>.","apa":"Nikfarjam, A., Neumann, A., Bossek, J., &#38; Neumann, F. (2022). Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tu\\v sar (Eds.), <i>Parallel Problem Solving from Nature (PPSN XVII)</i> (pp. 237–249). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">https://doi.org/10.1007/978-3-031-14714-2_17</a>","short":"A. Nikfarjam, A. Neumann, J. Bossek, F. Neumann, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tu\\v sar (Eds.), Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 237–249.","bibtex":"@inproceedings{Nikfarjam_Neumann_Bossek_Neumann_2022, place={Cham}, series={Lecture Notes in Computer Science}, title={Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">10.1007/978-3-031-14714-2_17</a>}, booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer International Publishing}, author={Nikfarjam, Adel and Neumann, Aneta and Bossek, Jakob and Neumann, Frank}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tu\\v sar, Tea}, year={2022}, pages={237–249}, collection={Lecture Notes in Computer Science} }","mla":"Nikfarjam, Adel, et al. “Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem.” <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 237–249, doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_17\">10.1007/978-3-031-14714-2_17</a>."},"place":"Cham","publication_identifier":{"isbn":["978-3-031-14714-2"]},"publication_status":"published","doi":"10.1007/978-3-031-14714-2_17","author":[{"first_name":"Adel","full_name":"Nikfarjam, Adel","last_name":"Nikfarjam"},{"last_name":"Neumann","full_name":"Neumann, Aneta","first_name":"Aneta"},{"first_name":"Jakob","full_name":"Bossek, Jakob","id":"102979","last_name":"Bossek","orcid":"0000-0002-4121-4668"},{"last_name":"Neumann","full_name":"Neumann, Frank","first_name":"Frank"}],"date_updated":"2023-12-13T10:49:51Z"},{"title":"Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods","doi":"10.1007/978-3-031-14714-2_1","publisher":"Springer International Publishing","date_updated":"2024-06-07T07:13:47Z","date_created":"2023-08-04T07:12:33Z","author":[{"last_name":"Prager","full_name":"Prager, Raphael Patrick","first_name":"Raphael Patrick"},{"first_name":"Moritz","last_name":"Seiler","full_name":"Seiler, Moritz","id":"105520"},{"orcid":"0000-0002-9788-8282","last_name":"Trautmann","full_name":"Trautmann, Heike","id":"100740","first_name":"Heike"},{"first_name":"Pascal","full_name":"Kerschke, Pascal","last_name":"Kerschke"}],"year":"2022","place":"Cham","citation":{"ieee":"R. P. Prager, M. Seiler, H. Trautmann, and P. Kerschke, “Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods,” in <i>Parallel Problem Solving from Nature — PPSN XVII</i>, 2022, pp. 3–17, doi: <a href=\"https://doi.org/10.1007/978-3-031-14714-2_1\">10.1007/978-3-031-14714-2_1</a>.","chicago":"Prager, Raphael Patrick, Moritz Seiler, Heike Trautmann, and Pascal Kerschke. “Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods.” In <i>Parallel Problem Solving from Nature — PPSN XVII</i>, edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tušar, 3–17. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_1\">https://doi.org/10.1007/978-3-031-14714-2_1</a>.","ama":"Prager RP, Seiler M, Trautmann H, Kerschke P. Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tušar T, eds. <i>Parallel Problem Solving from Nature — PPSN XVII</i>. Springer International Publishing; 2022:3–17. doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_1\">10.1007/978-3-031-14714-2_1</a>","bibtex":"@inproceedings{Prager_Seiler_Trautmann_Kerschke_2022, place={Cham}, title={Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-14714-2_1\">10.1007/978-3-031-14714-2_1</a>}, booktitle={Parallel Problem Solving from Nature — PPSN XVII}, publisher={Springer International Publishing}, author={Prager, Raphael Patrick and Seiler, Moritz and Trautmann, Heike and Kerschke, Pascal}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tušar, Tea}, year={2022}, pages={3–17} }","short":"R.P. Prager, M. Seiler, H. Trautmann, P. Kerschke, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 3–17.","mla":"Prager, Raphael Patrick, et al. “Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods.” <i>Parallel Problem Solving from Nature — PPSN XVII</i>, edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 3–17, doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_1\">10.1007/978-3-031-14714-2_1</a>.","apa":"Prager, R. P., Seiler, M., Trautmann, H., &#38; Kerschke, P. (2022). Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tušar (Eds.), <i>Parallel Problem Solving from Nature — PPSN XVII</i> (pp. 3–17). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_1\">https://doi.org/10.1007/978-3-031-14714-2_1</a>"},"page":"3–17","publication_identifier":{"isbn":["978-3-031-14714-2"]},"language":[{"iso":"eng"}],"_id":"46304","user_id":"15504","department":[{"_id":"34"},{"_id":"819"}],"abstract":[{"text":"In recent years, feature-based automated algorithm selection using exploratory landscape analysis has demonstrated its great potential in single-objective continuous black-box optimization. However, feature computation is problem-specific and can be costly in terms of computational resources. This paper investigates feature-free approaches that rely on state-of-the-art deep learning techniques operating on either images or point clouds. We show that point-cloud-based strategies, in particular, are highly competitive and also substantially reduce the size of the required solver portfolio. Moreover, we highlight the effect and importance of cost-sensitive learning in automated algorithm selection models.","lang":"eng"}],"editor":[{"first_name":"Günter","full_name":"Rudolph, Günter","last_name":"Rudolph"},{"full_name":"Kononova, Anna V.","last_name":"Kononova","first_name":"Anna V."},{"last_name":"Aguirre","full_name":"Aguirre, Hernán","first_name":"Hernán"},{"first_name":"Pascal","last_name":"Kerschke","full_name":"Kerschke, Pascal"},{"full_name":"Ochoa, Gabriela","last_name":"Ochoa","first_name":"Gabriela"},{"last_name":"Tušar","full_name":"Tušar, Tea","first_name":"Tea"}],"status":"public","type":"conference","publication":"Parallel Problem Solving from Nature — PPSN XVII"},{"place":"Cham","year":"2022","page":"192–206","citation":{"short":"J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann, in: G. Rudolph, A. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tušar (Eds.), Parallel Problem Solving from Nature — PPSN XVII, Springer International Publishing, Cham, 2022, pp. 192–206.","mla":"Heins, J., et al. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” <i>Parallel Problem Solving from Nature — PPSN XVII</i>, edited by G Rudolph et al., Springer International Publishing, 2022, pp. 192–206.","bibtex":"@inproceedings{Heins_Rook_Schäpermeier_Kerschke_Bossek_Trautmann_2022, place={Cham}, title={BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems}, booktitle={Parallel Problem Solving from Nature — PPSN XVII}, publisher={Springer International Publishing}, author={Heins, J and Rook, J and Schäpermeier, L and Kerschke, P and Bossek, Jakob and Trautmann, Heike}, editor={Rudolph, G and Kononova, AV and Aguirre, H and Kerschke, P and Ochoa, G and Tušar, T}, year={2022}, pages={192–206} }","apa":"Heins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J., &#38; Trautmann, H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In G. Rudolph, A. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tušar (Eds.), <i>Parallel Problem Solving from Nature — PPSN XVII</i> (pp. 192–206). Springer International Publishing.","ama":"Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G, Kononova A, Aguirre H, Kerschke P, Ochoa G, Tušar T, eds. <i>Parallel Problem Solving from Nature — PPSN XVII</i>. Springer International Publishing; 2022:192–206.","chicago":"Heins, J, J Rook, L Schäpermeier, P Kerschke, Jakob Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” In <i>Parallel Problem Solving from Nature — PPSN XVII</i>, edited by G Rudolph, AV Kononova, H Aguirre, P Kerschke, G Ochoa, and T Tušar, 192–206. Cham: Springer International Publishing, 2022.","ieee":"J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, and H. Trautmann, “BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems,” in <i>Parallel Problem Solving from Nature — PPSN XVII</i>, 2022, pp. 192–206."},"publication_identifier":{"isbn":["978-3-031-14714-2"]},"title":"BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems","date_updated":"2024-06-10T12:02:35Z","publisher":"Springer International Publishing","date_created":"2023-08-04T07:10:52Z","author":[{"last_name":"Heins","full_name":"Heins, J","first_name":"J"},{"last_name":"Rook","full_name":"Rook, J","first_name":"J"},{"first_name":"L","full_name":"Schäpermeier, L","last_name":"Schäpermeier"},{"first_name":"P","last_name":"Kerschke","full_name":"Kerschke, P"},{"orcid":"0000-0002-4121-4668","last_name":"Bossek","id":"102979","full_name":"Bossek, Jakob","first_name":"Jakob"},{"orcid":"0000-0002-9788-8282","last_name":"Trautmann","full_name":"Trautmann, Heike","id":"100740","first_name":"Heike"}],"editor":[{"last_name":"Rudolph","full_name":"Rudolph, G","first_name":"G"},{"first_name":"AV","full_name":"Kononova, AV","last_name":"Kononova"},{"full_name":"Aguirre, H","last_name":"Aguirre","first_name":"H"},{"last_name":"Kerschke","full_name":"Kerschke, P","first_name":"P"},{"full_name":"Ochoa, G","last_name":"Ochoa","first_name":"G"},{"last_name":"Tušar","full_name":"Tušar, T","first_name":"T"}],"status":"public","publication":"Parallel Problem Solving from Nature — PPSN XVII","type":"conference","language":[{"iso":"eng"}],"_id":"46302","department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504"}]
