HARD-DE: Hierarchical ARchive Based Mutation Strategy With Depth Information of Evolution for the Enhancement of Differential Evolution on Numerical Optimization
Differential evolution is a famous and effective branch of evolutionary computation, which aims at tackling complex optimization problems. There are two aspects significantly affecting the overall performance of DE variants, one is trial vector generation strategy and the other is the control parame...
Main Authors: | Zhenyu Meng, Jeng-Shyang Pan |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8615987/ |
Similar Items
-
Di-DE: Depth Information-Based Differential Evolution With Adaptive Parameter Control for Numerical Optimization
by: Zhenyu Meng, et al.
Published: (2020-01-01) -
Advanced Cauchy Mutation for Differential Evolution in Numerical Optimization
by: Tae Jong Choi, et al.
Published: (2020-01-01) -
A Multi-Angle Hierarchical Differential Evolution Approach for Multimodal Optimization Problems
by: Zhao Hong, et al.
Published: (2020-01-01) -
Global and local selection in differential evolution for constrained numerical optimization
by: Efrén Mezura-Montes, et al.
Published: (2009-10-01) -
Modeling of the Evolution of the Microstructure and the Hardness Penetration Depth for a Hypoeutectoid Steel Processed by Grind-Hardening
by: Yu Guo, et al.
Published: (2020-09-01)