In this paper, a novel differential evolution (DE) algorithm is proposed to improve the search
efficiency of DE by employing the information of individuals to adaptively set the parameters …

The introduction of a multi-population structure in differential evolution (DE) algorithm has
been proven to be an effective way to achieve algorithm adaptation and multi-strategy …

In this paper, we propose an improved version of JADE by hybridizing the JADE algorithm
with a Gaussian t ail, a modified hunger games search (HGS) algorithm, and a distance …

Differential Evolution (DE) algorithm is simple and effective. Since DE has been proposed, it
has been widely used to solve various complex optimization problems. To further exploit the …

Differential evolution (DE) is a simple and effective stochastic search algorithm, but its
convergence speed and population diversity often decline catastrophically with the evolution …

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 …

Differential evolution (DE) is an intelligent optimization algorithm inspired by biological
evolution. Setting a mutation strategy and control parameters that meet the optimization …

As an excellent optimization algorithm widely used to solve various practical problems,
differential evolution (DE) algorithm has few parameters, yet its performance is significantly …

Differential evolution (DE) algorithm has attracted considerable attention because of its
effectiveness and simplicity. However, previous studies have validated that DE still suffers …

The survivor selection operation is one of the factors affecting the performance of differential
evolution (DE) algorithms. However, in single-objective DE algorithms, researchers seldom …