---
_id: '46306'
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.
author:
- first_name: Lennart
  full_name: Schneider, Lennart
  last_name: Schneider
- first_name: Lennart
  full_name: Schäpermeier, Lennart
  last_name: Schäpermeier
- first_name: Raphael Patrick
  full_name: Prager, Raphael Patrick
  last_name: Prager
- first_name: Bernd
  full_name: Bischl, Bernd
  last_name: Bischl
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
- first_name: Pascal
  full_name: Kerschke, Pascal
  last_name: Kerschke
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>'
  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}
    }'
  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>.'
  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.'
date_created: 2023-08-04T07:15:16Z
date_updated: 2023-10-16T12:51:27Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-031-14714-2_40
editor:
- first_name: Günter
  full_name: Rudolph, Günter
  last_name: Rudolph
- first_name: Anna V.
  full_name: Kononova, Anna V.
  last_name: Kononova
- first_name: Hernán
  full_name: Aguirre, Hernán
  last_name: Aguirre
- first_name: Pascal
  full_name: Kerschke, Pascal
  last_name: Kerschke
- first_name: Gabriela
  full_name: Ochoa, Gabriela
  last_name: Ochoa
- first_name: Tea
  full_name: Tušar, Tea
  last_name: Tušar
language:
- iso: eng
page: 575–589
place: Cham
publication: Parallel Problem Solving from Nature — PPSN XVII
publication_identifier:
  isbn:
  - 978-3-031-14714-2
publisher: Springer International Publishing
status: public
title: 'HPO x ELA: Investigating Hyperparameter Optimization Landscapes by Means of
  Exploratory Landscape Analysis'
type: conference
user_id: '15504'
year: '2022'
...
---
_id: '48882'
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.
author:
- first_name: Jonathan
  full_name: Heins, Jonathan
  last_name: Heins
- first_name: Jeroen
  full_name: Rook, Jeroen
  last_name: Rook
- first_name: Lennart
  full_name: Schäpermeier, Lennart
  last_name: Schäpermeier
- first_name: Pascal
  full_name: Kerschke, Pascal
  last_name: Kerschke
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Heike
  full_name: Trautmann, Heike
  last_name: Trautmann
citation:
  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>'
  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>'
  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} }'
  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>.'
  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>.'
  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.'
date_created: 2023-11-14T15:58:58Z
date_updated: 2023-12-13T10:47:50Z
department:
- _id: '819'
doi: 10.1007/978-3-031-14714-2_14
editor:
- first_name: Günter
  full_name: Rudolph, Günter
  last_name: Rudolph
- first_name: Anna V.
  full_name: Kononova, Anna V.
  last_name: Kononova
- first_name: Hernán
  full_name: Aguirre, Hernán
  last_name: Aguirre
- first_name: Pascal
  full_name: Kerschke, Pascal
  last_name: Kerschke
- first_name: Gabriela
  full_name: Ochoa, Gabriela
  last_name: Ochoa
- first_name: Tea
  full_name: Tusar, Tea
  last_name: Tusar
extern: '1'
keyword:
- Anytime behavior
- Benchmarking
- Continuous optimization
- Multi-objective optimization
- Multimodality
- Performance metric
language:
- iso: eng
page: 192–206
place: Cham
publication: Parallel Problem Solving from Nature (PPSN XVII)
publication_identifier:
  isbn:
  - 978-3-031-14714-2
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: 'BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems'
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '48894'
abstract:
- lang: eng
  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.
author:
- first_name: Adel
  full_name: Nikfarjam, Adel
  last_name: Nikfarjam
- first_name: Aneta
  full_name: Neumann, Aneta
  last_name: Neumann
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Frank
  full_name: Neumann, Frank
  last_name: Neumann
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>'
  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>
  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} }'
  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>.'
  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>.'
  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>.
  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.'
date_created: 2023-11-14T15:59:00Z
date_updated: 2023-12-13T10:49:51Z
department:
- _id: '819'
doi: 10.1007/978-3-031-14714-2_17
editor:
- first_name: Günter
  full_name: Rudolph, Günter
  last_name: Rudolph
- first_name: Anna V.
  full_name: Kononova, Anna V.
  last_name: Kononova
- first_name: Hernán
  full_name: Aguirre, Hernán
  last_name: Aguirre
- first_name: Pascal
  full_name: Kerschke, Pascal
  last_name: Kerschke
- first_name: Gabriela
  full_name: Ochoa, Gabriela
  last_name: Ochoa
- first_name: Tea
  full_name: Tu\v sar, Tea
  last_name: Tu\v sar
extern: '1'
keyword:
- Co-evolutionary algorithms
- Evolutionary diversity optimisation
- Quality diversity
- Traveling thief problem
language:
- iso: eng
page: 237–249
place: Cham
publication: Parallel Problem Solving from Nature (PPSN XVII)
publication_identifier:
  isbn:
  - 978-3-031-14714-2
publication_status: published
publisher: Springer International Publishing
series_title: Lecture Notes in Computer Science
status: public
title: Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem
type: conference
user_id: '102979'
year: '2022'
...
---
_id: '46304'
abstract:
- lang: eng
  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.
author:
- first_name: Raphael Patrick
  full_name: Prager, Raphael Patrick
  last_name: Prager
- first_name: Moritz
  full_name: Seiler, Moritz
  id: '105520'
  last_name: Seiler
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
- first_name: Pascal
  full_name: Kerschke, Pascal
  last_name: Kerschke
citation:
  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>'
  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>'
  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} }'
  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>.'
  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>.'
  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>.'
  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.'
date_created: 2023-08-04T07:12:33Z
date_updated: 2024-06-07T07:13:47Z
department:
- _id: '34'
- _id: '819'
doi: 10.1007/978-3-031-14714-2_1
editor:
- first_name: Günter
  full_name: Rudolph, Günter
  last_name: Rudolph
- first_name: Anna V.
  full_name: Kononova, Anna V.
  last_name: Kononova
- first_name: Hernán
  full_name: Aguirre, Hernán
  last_name: Aguirre
- first_name: Pascal
  full_name: Kerschke, Pascal
  last_name: Kerschke
- first_name: Gabriela
  full_name: Ochoa, Gabriela
  last_name: Ochoa
- first_name: Tea
  full_name: Tušar, Tea
  last_name: Tušar
language:
- iso: eng
page: 3–17
place: Cham
publication: Parallel Problem Solving from Nature — PPSN XVII
publication_identifier:
  isbn:
  - 978-3-031-14714-2
publisher: Springer International Publishing
status: public
title: 'Automated Algorithm Selection in Single-Objective Continuous Optimization:
  A Comparative Study of Deep Learning and Landscape Analysis Methods'
type: conference
user_id: '15504'
year: '2022'
...
---
_id: '46302'
author:
- first_name: J
  full_name: Heins, J
  last_name: Heins
- first_name: J
  full_name: Rook, J
  last_name: Rook
- first_name: L
  full_name: Schäpermeier, L
  last_name: Schäpermeier
- first_name: P
  full_name: Kerschke, P
  last_name: Kerschke
- first_name: Jakob
  full_name: Bossek, Jakob
  id: '102979'
  last_name: Bossek
  orcid: 0000-0002-4121-4668
- first_name: Heike
  full_name: Trautmann, Heike
  id: '100740'
  last_name: Trautmann
  orcid: 0000-0002-9788-8282
citation:
  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.'
  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.'
  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} }'
  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.'
  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.'
  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.'
date_created: 2023-08-04T07:10:52Z
date_updated: 2024-06-10T12:02:35Z
department:
- _id: '34'
- _id: '819'
editor:
- first_name: G
  full_name: Rudolph, G
  last_name: Rudolph
- first_name: AV
  full_name: Kononova, AV
  last_name: Kononova
- first_name: H
  full_name: Aguirre, H
  last_name: Aguirre
- first_name: P
  full_name: Kerschke, P
  last_name: Kerschke
- first_name: G
  full_name: Ochoa, G
  last_name: Ochoa
- first_name: T
  full_name: Tušar, T
  last_name: Tušar
language:
- iso: eng
page: 192–206
place: Cham
publication: Parallel Problem Solving from Nature — PPSN XVII
publication_identifier:
  isbn:
  - 978-3-031-14714-2
publisher: Springer International Publishing
status: public
title: 'BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems'
type: conference
user_id: '15504'
year: '2022'
...