Enhancing the search ability of differential evolution through orthogonal crossover
Differential evolution (DE) is a class of simple yet powerful evolutionary algorithms for global
numerical optimization. Binomial crossover and exponential crossover are two commonly …
numerical optimization. Binomial crossover and exponential crossover are two commonly …
Enhancing differential evolution utilizing eigenvector-based crossover operator
SM Guo, CC Yang - IEEE Transactions on Evolutionary …, 2014 - ieeexplore.ieee.org
Differential evolution has been shown to be an effective methodology for solving
optimization problems over continuous space. In this paper, we propose an eigenvector …
optimization problems over continuous space. In this paper, we propose an eigenvector …
An adaptive differential evolution algorithm with population size reduction strategy for unconstrained optimization problem
X Zhang, Q Liu, Y Qu - Applied Soft Computing, 2023 - Elsevier
The differential evolution (DE) algorithm is a heuristic random search algorithm that
optimizes the problem based on population evolution. It has been widely studied for its …
optimizes the problem based on population evolution. It has been widely studied for its …
A population state evaluation-based improvement framework for differential evolution
Differential evolution (DE) is one of the most efficient evolutionary algorithms for solving
numerical optimization problems; however, it still suffers from premature convergence and …
numerical optimization problems; however, it still suffers from premature convergence and …
A trigonometric mutation operation to differential evolution
HY Fan, J Lampinen - Journal of global optimization, 2003 - Springer
Previous studies have shown that differential evolution is an efficient, effective and robust
evolutionary optimization method. However, the convergence rate of differential evolution in …
evolutionary optimization method. However, the convergence rate of differential evolution in …
Parameter and strategy adaptive differential evolution algorithm based on accompanying evolution
M Wang, Y Ma, P Wang - Information Sciences, 2022 - Elsevier
Differential evolution (DE) is an intelligent optimization algorithm inspired by biological
evolution. Setting a mutation strategy and control parameters that meet the optimization …
evolution. Setting a mutation strategy and control parameters that meet the optimization …
Exploring dynamic self-adaptive populations in differential evolution
J Teo - Soft computing, 2006 - Springer
Abstract Although the Differential Evolution (DE) algorithm has been shown to be a simple
yet powerful evolutionary algorithm for optimizing continuous functions, users are still faced …
yet powerful evolutionary algorithm for optimizing continuous functions, users are still faced …
Enhancing differential evolution utilizing proximity-based mutation operators
MG Epitropakis, DK Tasoulis… - IEEE Transactions …, 2011 - ieeexplore.ieee.org
Differential evolution is a very popular optimization algorithm and considerable research has
been devoted to the development of efficient search operators. Motivated by the different …
been devoted to the development of efficient search operators. Motivated by the different …
An adaptive regeneration framework based on search space adjustment for differential evolution
Differential evolution (DE) is a well-known evolutionary algorithm with simple operation and
excellent performance, which has been applied to solve various optimization problems. To …
excellent performance, which has been applied to solve various optimization problems. To …
An efficient differential evolution with fitness-based dynamic mutation strategy and control parameters
It is known that the performance of the differential evolution (DE) algorithm highly depends
on the mutation strategy and its control parameters. However, it is arduous to choose an …
on the mutation strategy and its control parameters. However, it is arduous to choose an …