Collective Foraging Mechanisms and Optimization Algorithms: A Review

In recent years, swarm intelligence research has rapidly advanced, leveraging biological self-organization mechanisms to create flexible, distributed, and robust self-organizing models and efficient metaheuristic optimization algorithms. Collective foraging behavior observed in nature serves as a significant source of inspiration for swarm intelligence. This paper surveys the swarm intelligence research inspired by biological collective foraging behavior. Firstly, it introduces typical self-organizing models based on collective foraging mechanisms and their applications, followed by a review of metaheuristic optimization algorithms inspired by collective foraging behavior. Finally, it outlines current research limitations and offers future prospects. The goal of this review is to assist researchers in comprehending swarm intelligence through a comprehensive and innovative lens by drawing upon natural inspirations.