AutoOpt: A General Framework for Automatically Designing Metaheuristic Optimization Algorithms With Diverse Structures

Metaheuristics are widely recognized gradient-free solvers to hard problems that do not meet the rigorous mathematical assumptions of conventional solvers. The automated design of metaheuristic algorithms provides an attractive path to relieve manual design effort and gain enhanced performance beyon...

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Vydáno v:	IEEE transactions on emerging topics in computational intelligence Ročník 9; číslo 5; s. 3690 - 3703
Hlavní autoři:	Zhao, Qi, Yan, Bai, Hu, Taiwei, Chen, Xianglong, Yang, Jian, Cheng, Shi, Shi, Yuhui
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 01.10.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms automated algorithm design automated machine learning Automation Binary trees Computer science evolutionary algorithm Genetic algorithms Graph representations Graphical representations Heuristic algorithms Heuristic methods Metaheuristic Metaheuristics optimization Performance enhancement Pipelines Problem-solving Prototypes Solvers Space exploration Vectors
ISSN:	2471-285X, 2471-285X
On-line přístup:	Získat plný text
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