Ant Colony Optimization

Ant Colony Optimization (ACO) is a metaheuristic algorithm inspired by the foraging behavior of ants, used to find approximate solutions to complex optimization problems. Current research focuses on improving ACO's efficiency for large-scale problems, exploring hybrid approaches that combine ACO with other algorithms like neural networks (e.g., GFlowNets) or Cohort Intelligence, and adapting ACO for specific applications such as route planning, robot navigation, and even natural language processing. These advancements demonstrate ACO's versatility and its potential to provide efficient solutions across diverse fields, impacting areas like transportation logistics, robotics, and artificial intelligence.