A fair performance comparison of different surrogate optimization strategies

Bernhard Werth; Erik Pitzer; Michael Affenzeller

doi:10.1007/978-3-319-74718-7_49

A fair performance comparison of different surrogate optimization strategies

Bernhard Werth, Erik Pitzer, Michael Affenzeller

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Much of the literature found on surrogate models presents new approaches or algorithms trying to solve black-box optimization problems with as few evaluations as possible. The comparisons of these new ideas with other algorithms are often very limited and constrained to non-surrogate algorithms or algorithms following very similar ideas as the presented ones. This work aims to provide both an overview over the most important general trends in surrogate assisted optimization and a more wide-spanning comparison in a fair environment by reimplementation within the same software framework.

Original language	English
Title of host publication	Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers
Editors	Roberto Moreno-Diaz, Alexis Quesada-Arencibia, Franz Pichler
Publisher	Springer
Pages	408-415
Number of pages	8
ISBN (Print)	9783319747170
DOIs	https://doi.org/10.1007/978-3-319-74718-7_49
Publication status	Published - 2018
Event	16th International Conference on Computer Aided Systems Theory, EUROCAST 2017 - Las Palmas de Gran Canaria, Spain Duration: 19 Feb 2017 → 24 Feb 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10671 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Computer Aided Systems Theory, EUROCAST 2017
Country/Territory	Spain
City	Las Palmas de Gran Canaria
Period	19.02.2017 → 24.02.2017

Keywords

Black-box optimization
Evolutionary algorithms
Surrogate models

Access to Document

10.1007/978-3-319-74718-7_49

Cite this

Werth, B., Pitzer, E., & Affenzeller, M. (2018). A fair performance comparison of different surrogate optimization strategies. In R. Moreno-Diaz, A. Quesada-Arencibia, & F. Pichler (Eds.), Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers (pp. 408-415). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10671 LNCS). Springer. https://doi.org/10.1007/978-3-319-74718-7_49

Werth, Bernhard ; Pitzer, Erik ; Affenzeller, Michael. / A fair performance comparison of different surrogate optimization strategies. Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers. editor / Roberto Moreno-Diaz ; Alexis Quesada-Arencibia ; Franz Pichler. Springer, 2018. pp. 408-415 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A fair performance comparison of different surrogate optimization strategies",

abstract = "Much of the literature found on surrogate models presents new approaches or algorithms trying to solve black-box optimization problems with as few evaluations as possible. The comparisons of these new ideas with other algorithms are often very limited and constrained to non-surrogate algorithms or algorithms following very similar ideas as the presented ones. This work aims to provide both an overview over the most important general trends in surrogate assisted optimization and a more wide-spanning comparison in a fair environment by reimplementation within the same software framework.",

keywords = "Black-box optimization, Evolutionary algorithms, Surrogate models",

author = "Bernhard Werth and Erik Pitzer and Michael Affenzeller",

note = "Funding Information: Acknowledgements. This work was supported by the European Union through the European Regional Development Fund (EFRE; further information on IWB/EFRE is available at www.efre.gv.at). Funding Information: This work was supported by the European Union through the European Regional Development Fund (EFRE; further information on IWB/EFRE is available at www.efre.gv.at). Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.; 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017 ; Conference date: 19-02-2017 Through 24-02-2017",

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language = "English",

isbn = "9783319747170",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Werth, B , Pitzer, E & Affenzeller, M 2018, A fair performance comparison of different surrogate optimization strategies. in R Moreno-Diaz, A Quesada-Arencibia & F Pichler (eds), Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10671 LNCS, Springer, pp. 408-415, 16th International Conference on Computer Aided Systems Theory, EUROCAST 2017, Las Palmas de Gran Canaria, Spain, 19.02.2017. https://doi.org/10.1007/978-3-319-74718-7_49

A fair performance comparison of different surrogate optimization strategies. / Werth, Bernhard ; Pitzer, Erik ; Affenzeller, Michael.
Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers. ed. / Roberto Moreno-Diaz; Alexis Quesada-Arencibia; Franz Pichler. Springer, 2018. p. 408-415 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10671 LNCS).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

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AU - Werth, Bernhard

AU - Pitzer, Erik

AU - Affenzeller, Michael

N1 - Funding Information: Acknowledgements. This work was supported by the European Union through the European Regional Development Fund (EFRE; further information on IWB/EFRE is available at www.efre.gv.at). Funding Information: This work was supported by the European Union through the European Regional Development Fund (EFRE; further information on IWB/EFRE is available at www.efre.gv.at). Publisher Copyright: © Springer International Publishing AG 2018.

PY - 2018

Y1 - 2018

N2 - Much of the literature found on surrogate models presents new approaches or algorithms trying to solve black-box optimization problems with as few evaluations as possible. The comparisons of these new ideas with other algorithms are often very limited and constrained to non-surrogate algorithms or algorithms following very similar ideas as the presented ones. This work aims to provide both an overview over the most important general trends in surrogate assisted optimization and a more wide-spanning comparison in a fair environment by reimplementation within the same software framework.

AB - Much of the literature found on surrogate models presents new approaches or algorithms trying to solve black-box optimization problems with as few evaluations as possible. The comparisons of these new ideas with other algorithms are often very limited and constrained to non-surrogate algorithms or algorithms following very similar ideas as the presented ones. This work aims to provide both an overview over the most important general trends in surrogate assisted optimization and a more wide-spanning comparison in a fair environment by reimplementation within the same software framework.

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KW - Evolutionary algorithms

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BT - Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers

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Werth B , Pitzer E , Affenzeller M. A fair performance comparison of different surrogate optimization strategies. In Moreno-Diaz R, Quesada-Arencibia A, Pichler F, editors, Computer Aided Systems Theory – EUROCAST 2017 - 16th International Conference, Revised Selected Papers. Springer. 2018. p. 408-415. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-74718-7_49

A fair performance comparison of different surrogate optimization strategies

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A fair performance comparison of different surrogate optimization strategies

Abstract

Publication series

Conference

Keywords

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Fingerprint

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Connected Vehicles

Cite this