Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem
Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem Introduction The Traveling Salesman Problem (TSP) is a classic optimization challenge where a salesman must visit a set of cities exactly once and return to the starting point, minimizing the total travel distance. Traditional algorithms struggle with large-scale instances due to the NP-hard nature of the problem. Ant Colony Optimization (ACO) , inspired by real ants' foraging behavior, offers an intelligent heuristic approach to solving the TSP efficiently. This blog explores the Ant Colony System (ACS) as proposed by Dorigo & Gambardella (1997) and presents a step-by-step implementation in Python. Understanding Ant Colony System (ACS) The Ant Colony System (ACS) is an improved version of ACO that enhances performance by introducing: Pheromone Update Mechanisms: A balance between local and global updates. Pheromone Evaporatio...