Global convergence limits of differential evolution algorithm
Roman Knobloch, Jaroslav Mlýnek · 2024
In a recent period, evolutionary optimization techniques have been increasingly utilized for solving technical and scientific optimization tasks. The differential evolution algorithm is one of the most used optimization tools. This specific algorithm is often and in many published sources classified as a global optimizer. Such statements indicate that the differential evolution algorithm can identify the global minimum of a specific cost function. In the article, we demonstrate rigorously and in a simple way that in some special circumstances, this algorithm fails and is prone to premature convergence to a local minimum of the cost function.