Data-Driven Evolutionary Optimization: An Overview and Case Studies

Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however, such objective functions may not exist. Instead, computationally expensive numerical simulations or costly phy...

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Vydané v:	IEEE transactions on evolutionary computation Ročník 23; číslo 3; s. 442 - 458
Hlavní autori:	Jin, Yaochu, Wang, Handing, Chugh, Tinkle, Guo, Dan, Miettinen, Kaisa
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.06.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Computational modeling Computer simulation Data mining Data models Data science data-driven optimization Evolutionary algorithms evolutionary algorithms (EAs) Fitness Machine learning model management Optimization Sociology Statistics surrogate Taxonomy
ISSN:	1089-778X, 1941-0026
On-line prístup:	Získať plný text
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