It is well known that mutation scale factor, the crossover constant, and the population size
are three main control parameters of the differential evolution (DE) algorithm. These …

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 …

Many real-world optimization problems are difficult to solve as they do not possess the nice
mathematical properties required by the exact algorithms. Evolutionary algorithms are …

Differential evolution (DE) is a popular evolutionary technique which can be applied in
various constrained and unconstrained optimization problems along with the real time …

Differential evolution (DE) is a simple yet effective metaheuristic specially suited for real-
parameter optimization. The most advanced DE variants take into account the feedback …

Differential Evolution (DE) is a simple and effective approach for solving numerical
optimization problems. However, the performance of DE is sensitive to the choice of the …

Differential evolution (DE) algorithm has been shown to be a simple and efficient
evolutionary algorithm for global optimization over continuous spaces, and has been widely …

Many practical engineering applications can be formulated as a global optimization
problem, in which objective function has many local minima, and derivatives of the objective …

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) has become a very popular and effective global optimization
algorithm in the area of evolutionary computation. In spite of many advantages such as …