Module 14: Ant Colony Optimization - Pheromone Trails and Collective Problem-Solving

Ants solve TSP better than most CS students. ACO uses artificial pheromones to guide a colony of agents through combinatorial search spaces. It's the go-to method for routing, scheduling, and graph optimization problems.

Learning Objectives

1. Implement Ant System (AS) for TSP from scratch
2. Understand pheromone deposit and evaporation dynamics
3. Code Ant Colony System (ACS) with local pheromone updates
4. Implement MMAS (Max-Min Ant System)
5. Apply ACO to a real graph/routing problem

Concept Explanation

Coming soon.

Code Examples

Coming soon.

Exercises

Coming soon.

Milestone Checklist

• Built AS for TSP
• Understand pheromone evaporation trade-offs
• Implemented ACS or MMAS
• Solved a routing problem with ACO