A comprehensive review of hybrid variants of artificial bee colony algorithm
Gurmeet Saini, Shimpi Singh Jadon · 2025
Inspired by the astute foraging habits of honeybees, the artificial bee colony (ABC) algorithm is a well-known swarm-based optimization method. However, ABC has its limitations, such as slow convergence, struggling with complex problems, or getting trapped in local optima due to insufficient exploration, aiming to mitigate these shortcomings. Over time, various swarm intelligence-based optimization techniques have emerged, demonstrating their efficacy. The pursuit of optimization methodologies has led to the evolution of the ABC algorithm, prompting the development of its hybrid variants. This comprehensive review investigates the landscape of these hybrid adaptations, exploring their integration with diverse optimization paradigms. Spanning various domains and applications, this analysis illuminates the advancements, strengths, and applications of these hybrid ABC algorithms. The synthesis of this survey provides a profound understanding of the innovative combination of ABC with diverse optimization techniques, fostering a roadmap for future research directions.