HyperDE: An Adaptive Hyper-Heuristic for Global Optimization

In this paper, a novel global optimization approach in the form of an adaptive hyper-heuristic, namely HyperDE, is proposed. As naming suggests, method based on Differential Evolution (DE) heuristic, which well-established inspired by theory evolution. Additionally, two other similar approaches are introduced for comparison and validation, HyperSSA HyperBES, Sparrow Search Algorithm (SSA) Bald Eagle (BES), respectively. The consists genetic algorithm that adopted as high-level online learning mechanism, order to adjust hyper-parameters facilitate collaboration homogeneous set low-level heuristics with intent maximizing performance search optima. Comparison proposed methodologies on, along state-of-the-art methods, favorable.