Addition of out-of-population search based on the rate of solution updates in JADE

Abstract

JADE is an optimization algorithm that uses probability distributions to adaptively select parameters. However, it does not take into account the search for regions outside the solution population, so it can be improved by adding an efficient out-of-population search such as the Nelder-Mead method. In this study, a simple method with a small number of parameters to add out-of-population search was considered while keeping the search speed as high as possible, and its effectiveness was confirmed through numerical experiments.