Differential Evolution (DE) is a simple and efficient optimizer, especially for continuous
optimization. For these reasons DE has often been employed for solving various …

The area of metaheuristics has grown immensely in the past two decades as a solution to
real-world optimisation problems. They are able to perform well in situations where exact …

Differential evolution is an effective and practical approach that is widely applied for solving
global optimization problems. Nevertheless, its effectiveness and scalability are decreased …

Differential evolution (DE) is one of the most popular and efficient evolutionary algorithms for
numerical optimization and it has gained much success in a series of academic benchmark …

Global optimization of cluster geometries is of fundamental importance in chemistry and an
interesting problem in applied mathematics. In this work, we introduce a relatively new …

The global optimization of molecular clusters is an important topic encountered in many
fields of chemistry. In our previous work (Phys. Chem. Chem. Phys., 2015, 17, 24173), we …

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter
optimization algorithms in current use. DE operates through similar computational steps as …

Proposing new mutation strategies to improve the optimization performance of differential
evolution (DE) is an important research study. Therefore, the main contribution of this paper …

Trial vector generation strategies and control parameters have a significant influence on the
performance of differential evolution (DE). This paper studies whether the performance of …

This paper studies the problem of simultaneously aligning a batch of linearly correlated
images despite gross corruption (such as occlusion). Our method seeks an optimal set of …