Differential Evolution (DE) is a powerful population-based evolutionary algorithm for global
optimization, and it is widely used in many scientific and engineering applications. There are …

Differential evolution (DE) is a simple and efficient global optimization algorithm. It has been
successfully applied to solve a wide range of real-world optimization problems. However …

Differential evolution (DE) is a class of simple yet powerful evolutionary algorithms for global
numerical optimization. Binomial crossover and exponential crossover are two commonly …

Differential evolution (DE) is a simple, yet efficient, evolutionary algorithm for global
numerical optimization, which has been widely used in many areas. However, the choice of …

Previous studies have shown that differential evolution is an efficient, effective and robust
evolutionary optimization method. However, the convergence rate of differential evolution in …

Over the last few decades, a number of differential evolution (DE) algorithms have been
proposed with excellent performance on mathematical benchmarks. However, like any other …

Differential evolution (DE) has been a simple yet effective algorithm for global optimization
problems. The performance of DE highly depends on its operators and parameter settings …

The differential evolution algorithm (DE) is a simple and effective global optimization
algorithm. It has been successfully applied to solve a wide range of real-world optimization …

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