Abstract
The Honey Badger Algorithm (HBA) is a recent addition to the growing family of nature-inspired optimization techniques within the domain of Swarm Intelligence (SI). Inspired by the intelligent foraging behavior of honey badgers, HBA has demonstrated remarkable effectiveness in solving complex optimization problems. This review provides an analysis of HBA, exploring its core principles, applications (particularly within the engineering domain), and the evolution of the algorithm through various modified and hybrid versions. The authors further leverage bibliometric analysis to unveil research trends and offer valuable insights into the current state of HBA research. Finally, this study provides insights for future advancements and applications in diverse problem-solving tasks while harnessing the HBA.