Surrogate Modeling in the Evolutionary Optimization of Catalytic Materials
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F12%3A00380963" target="_blank" >RIV/67985807:_____/12:00380963 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Surrogate Modeling in the Evolutionary Optimization of Catalytic Materials
Original language description
The search for best performing catalysts leads to high-dimensional optimization tasks. They are by far most frequently tackled using evolutionary algorithms, usually implemented in systems developed specifically for the area of catalysis. Their fitness functions are black-box functions with costly and time-consuming empirical evaluation. This suggests to apply surrogate modeling. The paper points out three difficulties challenging the application of surrogate modeling to catalysts optimization: mixed-variables optimization, assessing the suitability of different models, and scalarization of multiple objectives. It then provides examples of how those challenges are tackled in real-world catalysts optimization tasks. The examples are based on results obtained in three such tasks using one of specific evolutionary optimization systems for catalysis.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
GECCO '12. Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference
ISBN
978-1-4503-1177-9
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1095-1102
Publisher name
ACM
Place of publication
New York
Event location
Philadelphia
Event date
Jul 7, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000309611100137