Vehicle Routing Problem (VRP) Solution Using Ant Colony Algorithm

This code provides a solution for the Vehicle Routing Problem (VRP) using Ant Colony Optimization algorithm.

The algorithm mimics the foraging behavior of ants by simulating multiple artificial ants searching through the solution space to find optimal routes. Specifically, the problem is modeled as a graph where artificial ants traverse nodes representing customer locations. During the search process, each ant randomly navigates through the graph while depositing pheromone trails on visited paths. Subsequent ants probabilistically select paths based on pheromone intensity and heuristic information (e.g., distance between nodes). After completing a route, the ants reinforce the pheromone levels on high-quality paths while allowing evaporation to avoid local optima. The implementation includes key components such as: 1) Graph initialization with distance matrices, 2) Pheromone matrix management with evaporation rates, 3) Path selection using probability calculations combining pheromone and heuristic values, and 4) Iterative optimization through colony-wide coordination.

By applying this bio-inspired algorithm to VRP, the code efficiently explores feasible vehicle routes while minimizing total travel distance or other specified objectives through iterative refinement.