A Review on Evolutionary Multitask Optimization: Trends and Challenges

Evolutionary algorithms (EAs) possess strong problem-solving abilities and have been applied in a wide range of applications. However, they still suffer from a high computational burden and poor generalization ability. To overcome the limitations, numerous studies consider conducting knowledge extra...

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Vydáno v:IEEE transactions on evolutionary computation Ročník 26; číslo 5; s. 941 - 960
Hlavní autoři: Wei, Tingyang, Wang, Shibin, Zhong, Jinghui, Liu, Dong, Zhang, Jun
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.10.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Costs
Evolutionary algorithm (EA)
Evolutionary algorithms
Evolutionary computation
evolutionary multitasking
Multitasking
Optimization
Sociology
Statistics
Task analysis
transfer optimization
Trends
ISSN:1089-778X, 1941-0026
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Shrnutí:Evolutionary algorithms (EAs) possess strong problem-solving abilities and have been applied in a wide range of applications. However, they still suffer from a high computational burden and poor generalization ability. To overcome the limitations, numerous studies consider conducting knowledge extraction across distinct optimization task domains. Among these research strands, one representative tributary is evolutionary multitask optimization (EMTO) that aims to resolve multiple optimization tasks simultaneously. The underlying attribute of implicit parallelism for EAs can well incorporate with the framework of EMTO, giving rise to the ascending EMTO studies. This review is intended to present a detailed exposition on the research in the EMTO area. We reveal the core components for designing the EMTO algorithms. Subsequently, we organize the works lying in the fusions between EMTO and traditional EAs. By analyzing the associations for diverse strategies in different branches of EMTO, this review uncovers the research trends and the potentially important directions, with additional interesting real-world applications mentioned.
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ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2021.3139437