Differential evolution (DE) algorithm has been shown to be a very effective and efficient
approach for solving global numerical optimization problems, which attracts a great attention …

In differential evolution (DE) research, many successful empirical guidelines in selecting
appropriate trial vector generation strategies and control parameter values for various …

Abstract The performance of Differential Evolution is significantly affected by the mutation
scheme, which attracts many researchers to develop and enhance the mutation scheme in …

Differential evolution (DE) is a simple yet powerful evolutionary algorithm that has been
used to solve various complex optimization problems in numerous engineering fields …

Differential Evolution (DE) is currently one of the most competitive Evolutionary Algorithms
(EAs) for optimization problems involving continuous parameters. This article presents three …

Differential evolution (DE) is a simple yet efficient evolutionary algorithm for real‐world
engineering problems. However, its search ability should be further enhanced to obtain …

Past few decades have witnessed the growth and development of different optimization
techniques that can be applied for solving complex problems that are otherwise difficult to …

This paper proposes a novel adaptation scheme for Differential Evolution (DE) frameworks.
The proposed algorithm, namely Estimation Distribution Differential Evolution (EDDE), is …

Differential evolution (DE) is a simple and efficient technique for real parameter optimization
over continuous spaces. Its success is highly dependent on the choice of correct trial vector …

Differential Evolution (DE) has been proven to be an efficient and robust algorithm for many
real optimization problems. However, it still may converge toward local optimum solutions …