Publication

Abstract : This chapter offers a unique perspective on leveraging bee-inspired algorithms for tackling complex problems in multi-objective and dynamic optimization domains. It takes readers on a journey through the intricate world of swarm intelligence, drawing parallels between the collaborative behavior of bees in a hive and the optimization processes required in dynamic and multi-objective scenarios. By adopting a “bee-eye view,” the text likely explores how collective decision-making and communication within a swarm can be translated into effective algorithms for addressing optimization challenges. Expect the summary to delve into practical applications and case studies that showcase the efficacy of these bee-inspired strategies in real-world scenarios. The chapter likely emphasizes the adaptability of swarm intelligence algorithms in dynamic environments and their ability to find optimal solutions when dealing with multiple, often conflicting, objectives.