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 the most efficient evolutionary algorithm widely used to solve
continuous or discrete numerical optimization problems. However, the performance of DE …

In recent years, Differential Evolution (DE) has shown excellent performance in solving
optimization problems over continuous space and has been widely used in many fields of …

The performance of differential evolution (DE) algorithm heavily depends on the
evolutionary scale, which is controlled by the generation operations including mutation …

Differential evolution (DE) is a powerful evolutionary algorithm (EA) for numerical
optimization. It has been successfully used in various scientific and engineering fields. In …

In recent years, many different differential evolution (DE) variants have been proposed to
solve real-world optimization problems. However, the performance of them is largely …

Differential evolution (DE) is a simple yet powerful evolutionary algorithm for numerical
optimization. However, the performance of DE significantly relies on its mutation operator …

Differential evolution (DE) is recognized as a simple but powerful algorithm in the family of
evolutionary algorithms. Over the past two decades, many advanced DE variants with …

Differential evolution (DE) algorithms have been used widely to solve optimization problems
and practical cases and have demonstrated high efficiency, performing favorably using only …

An effective and efficient successful-parent-selecting framework is proposed to improve the
performance of differential evolution (DE) by providing an alternative for the selection of …