More than a decade after the first extensive overview on parameter control, we revisit the
field and present a survey of the state-of-the-art. We briefly summarize the development of …

Differential evolution (DE) is a well-known optimization algorithm that utilizes the difference
of positions between individuals to perturb base vectors and thus generate new mutant …

Differential evolution (DE) is an efficient and robust evolutionary algorithm, which has been
widely applied to solve global optimization problems. As we know, crossover operator plays …

In differential evolution (DE) studies, there are many parameter adaptation methods, aiming
at tuning the mutation factor F and the crossover probability CR. However, these methods …

Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA) for global
numerical optimization. However, its performance is significantly influenced by its …

Over the past few years, differential evolution (DE) is generally considered as a reliable,
accurate and robust population-based evolutionary algorithm (EA). It is capable of handling …

Economic load dispatch (ELD) is an important constrained optimization task addressing this
vital concern for power system operations. ELD problem is the process of allocating …

In this paper, a new hybrid population based algorithm (DE-FPA) is proposed with the
combination of differential evolution optimization algorithm and flower pollination algorithm …

Evolutionary algorithms (EAs) have yielded promising results for solving nonlinear, non-
differentiable and multi-modal optimization problems. Due to its population-based nature …

Nowadays, differential evolution (DE) has attracted more and more attention as an effective
approach for solving numerical optimization problems. However, the fact that users have to …