If You Can’t Beat It, Squash It: Simplify Global Optimization by Evolving Dilation Functions

Author:

Papetti Daniele M.,Ashlock Daniel A.,Cazzaniga Paolo,Besozzi Daniela,Nobile Marco S.

Publisher

IEEE

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Evolving Dilation Functions for Parameter Estimation;2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB);2023-08-29

2. The Domination Game: Dilating Bubbles to Fill Up Pareto Fronts;2023 IEEE Congress on Evolutionary Computation (CEC);2023-07-01

3. Simplifying Fitness Landscapes Using Dilation Functions Evolved With Genetic Programming;IEEE Computational Intelligence Magazine;2023-02

4. Local Bubble Dilation Functions: Hypersphere-bounded Landscape Deformations Simplify Global Optimization;2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB);2022-08-15

5. Using Average-Fitness Based Selection to Combat the Curse of Dimensionality;2022 IEEE Congress on Evolutionary Computation (CEC);2022-07-18

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