Differential Evolution (DE) is a simple and efficient optimizer, especially for continuous
optimization. For these reasons DE has often been employed for solving various …

Data clustering is the process of identifying natural groupings or clusters within
multidimensional data based on some similarity measure. Clustering is a fundamental …

Differential evolution (DE) is among the most efficient evolutionary algorithms (EAs) for
global optimization and now widely applied to solve diverse real-world applications. As the …

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter
optimization algorithms in current use. DE operates through similar computational steps as …

Proposing new mutation strategies to improve the optimization performance of differential
evolution (DE) is an important research study. Therefore, the main contribution of this paper …

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 …

Differential evolution (DE) is an efficient and powerful population-based stochastic search
technique for solving optimization problems over continuous space, which has been widely …

This paper presents adaptive guided differential evolution algorithm (AGDE) for solving
global numerical optimization problems over continuous space. In order to utilize the …

Differential evolution (DE) is well known as a simple and efficient scheme for global
optimization over continuous spaces. It has reportedly outperformed a few evolutionary …

In classification problems, normally there exists a large number of features, but not all of
them contributing to the improvement of classification performance. These redundant …