Automated Design of Metaheuristics Using Reinforcement Learning Within a Novel General Search Framework

Metaheuristic algorithms have been investigated intensively to address highly complex combinatorial optimization problems. However, most metaheuristic algorithms have been designed manually by researchers of different expertise without a consistent framework. This article proposes a general search f...

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Veröffentlicht in:IEEE transactions on evolutionary computation Jg. 27; H. 4; S. 1072 - 1084
Hauptverfasser: Yi, Wenjie, Qu, Rong, Jiao, Licheng, Niu, Ben
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.08.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1089-778X, 1941-0026
Online-Zugang:Volltext
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