Generalized Multitasking for Evolutionary Optimization of Expensive Problems

Conventional evolutionary algorithms (EAs) are not well suited for solving expensive optimization problems due to the fact that they often require a large number of fitness evaluations to obtain acceptable solutions. To alleviate the difficulty, this paper presents a multitasking evolutionary optimi...

Celý popis

Podrobná bibliografie

Vydáno v:	IEEE transactions on evolutionary computation Ročník 23; číslo 1; s. 44 - 58
Hlavní autoři:	Ding, Jinliang, Yang, Cuie, Jin, Yaochu, Chai, Tianyou
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.02.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Convergence Evolutionary algorithms Evolutionary algorithms (EAs) Evolutionary computation evolutionary multitasking optimization expensive optimization Fitness Knowledge management Knowledge transfer Multitasking Optimization Sociology Statistics
ISSN:	1089-778X, 1941-0026
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!