Investigating innovized progress operators with different machine learning methods

Enhancing the convergence ability of evolutionary multi-objective optimization algorithms with momentum

L Chen, LM Pang, Q Zhang, H Ishibuchi - Proceedings of the Genetic …, 2024 - dl.acm.org
To improve the convergence ability of evolutionary multi-objective optimization algorithms
(EMOAs), various strategies have been proposed. One effective strategy is to use good …
被引用次数：1 相关文章 所有 3 个版本

Learning to Converge Better: IP2 Operator

DK Saxena, S Mittal, K Deb, ED Goodman - Machine Learning Assisted …, 2024 - Springer
In the context of online innovization (Section 3.1. 2, Chapter 3), it has been discussed that
inter-variable relationships with pre-specified structures can be extracted in any intermediate …
相关文章

Learning to Diversify Better: IP3 Operator

DK Saxena, S Mittal, K Deb, ED Goodman - Machine Learning Assisted …, 2024 - Springer
It was emphasized earlier that evolutionary multi-and many-objective optimization
algorithms, jointly referred to as EMâOAs, pursue the dual goals of convergence to and …
相关文章

Investigating Innovized Progress Operators with Different ML Methods

DK Saxena, S Mittal, K Deb, ED Goodman - Machine Learning Assisted …, 2024 - Springer
Chapters 5 and 6 have shown how learning efficient search directions from the intermittent
generations' solutions could be utilized to create pro-convergence and pro-diversity …
相关文章