Abstract

This research explores Swarm Intelligence algorithms, an advanced field in artificial intelligence that mimics the collective behavior of organisms like ants and bees to solve complex problems. The Ant Colony Optimization (ACO) algorithm models ant foraging behavior to solve path optimization problems such as the Traveling Salesman Problem (TSP). The Bee Algorithm mimics bee foraging behavior for resource optimization. A case study compares the performance of ACO and the Bee Algorithm in optimizing transportation routes, evaluating their speed, accuracy, and ability to handle complexity.