Ant Colony Optimization for Traveling Salesman Problem (TSP)

Idea: Solve the Traveling Salesman Problem (TSP) using Ant Colony Optimization (ACO) inspired by how ants find shortest paths.

Method:

Multiple “ants” explore possible city routes.

Paths are evaluated by distance and reinforced with pheromone trails.

Over iterations, ants converge to near-optimal shortest routes.

Tools: Python, NumPy, Matplotlib.

Outcome: Efficiently finds short paths in TSP instances, showing how nature-inspired algorithms can solve complex optimization problems.

Importance: Demonstrates Swarm Intelligence and its application to real-world routing/logistics.