Di-DE: Depth Information-Based Differential Evolution With Adaptive Parameter Control for Numerical Optimization

Di-DE: Depth Information-Based Differential Evolution With Adaptive Parameter Control for Numerical Optimization

Differential Evolution (DE) is a simple and effective stochastic algorithm for optimization problems, and it became much more popular in recent year because of its easy-implementation and excellent performance. Nevertheless, the performance of DE algorithm is greatly affected by the trial vector gen...

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Bibliographic Details
Main Authors: Zhenyu Meng, Cheng Yang, Xiaoqing Li, Yuxin Chen
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Depth information
differential evolution
numerical optimization
parameter control
stochastic optimization
Online Access:https://ieeexplore.ieee.org/document/9015955/

Internet

https://ieeexplore.ieee.org/document/9015955/

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