An evolving surrogate model-based differential evolution algorithm
R Mallipeddi, M Lee - Applied Soft Computing, 2015 - Elsevier
Differential evolution (DE) is a simple and effective approach for solving numerical
optimization problems. However, the performance of DE is sensitive to the choice of …
optimization problems. However, the performance of DE is sensitive to the choice of …
Surrogate model assisted ensemble differential evolution algorithm
R Mallipeddi, M Lee - 2012 IEEE congress on evolutionary …, 2012 - ieeexplore.ieee.org
Differential Evolution (DE) is a simple and effective approach for solving numerical
optimization problems. However, the performance of DE is sensitive to the choice of the …
optimization problems. However, the performance of DE is sensitive to the choice of the …
Differential evolution algorithm with ensemble of parameters and mutation strategies
Differential evolution (DE) has attracted much attention recently as an effective approach for
solving numerical optimization problems. However, the performance of DE is sensitive to the …
solving numerical optimization problems. However, the performance of DE is sensitive to the …
A new self-adaptation scheme for differential evolution
Abstract The performance of Differential Evolution (DE) largely depends on the choice of trial
vector generation strategy and the values of its control parameters. In the past years, quite a …
vector generation strategy and the values of its control parameters. In the past years, quite a …
Differential evolution algorithm with ensemble of parameters and mutation and crossover strategies
R Mallipeddi, PN Suganthan - … 2010, Chennai, India, December 16-18 …, 2010 - Springer
Differential Evolution (DE) has attracted much attention recently as an effective approach for
solving numerical optimization problems. However, the performance of DE is sensitive to the …
solving numerical optimization problems. However, the performance of DE is sensitive to the …
Enhanced differential evolution with adaptive strategies for numerical optimization
Differential evolution (DE) is a simple, yet efficient, evolutionary algorithm for global
numerical optimization, which has been widely used in many areas. However, the choice of …
numerical optimization, which has been widely used in many areas. However, the choice of …
A self-adaptive multi-population differential evolution algorithm
L Zhu, Y Ma, Y Bai - Natural Computing, 2020 - Springer
Differential evolution (DE) is an efficient population-based search algorithm for solving
numerical optimization problems. However, the performance of DE is very sensitive to the …
numerical optimization problems. However, the performance of DE is very sensitive to the …
Differential evolution with individual-dependent and dynamic parameter adjustment
Differential evolution (DE) is a powerful and versatile evolutionary algorithm for global
optimization over continuous search space, whose performance is significantly influenced …
optimization over continuous search space, whose performance is significantly influenced …
An adaptive differential evolution with combined strategy for global numerical optimization
G Sun, B Yang, Z Yang, G Xu - Soft Computing, 2020 - Springer
Differential evolution (DE) is a simple yet powerful evolutionary algorithm for numerical
optimization. However, the performance of DE significantly relies on its mutation operator …
optimization. However, the performance of DE significantly relies on its mutation operator …
Multi-search differential evolution algorithm
X Li, S Ma, J Hu - Applied Intelligence, 2017 - Springer
The differential evolution algorithm (DE) has been shown to be a very simple and effective
evolutionary algorithm. Recently, DE has been successfully used for the numerical …
evolutionary algorithm. Recently, DE has been successfully used for the numerical …