Hill climbing algorithm with honey badger algorithm for global numerical optimization

The Honey Badger Algorithm (HBA) is an optimization algorithm that works under limitations such as trapping in local optima, slow convergence, and loss of diversity. This research benefits HBA by making better exploration, and exploitation and increasing the convergence rate of the exploration-exploitation process. The Hill Climbing algorithm is incorporated also to avoid getting trapped into a local optimum, and new selection methods are proposed to ensure disparate solutions are generated. To the true test, the enhanced HBA was applied to real-life engineering problems to establish that convergence rates were faster, that search methods were more efficient, and that the solutions obtained were superior. The results indicate that the improved HBA is superior as well as more feasible for different optimization problems, providing far greater advancements over the initial algorithm.