MATLAB Source Code for Solving Traveling Salesman Problem Using Ant Colony Optimization Algorithm
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Resource Overview
MATLAB implementation of Ant Colony Optimization for solving the Traveling Salesman Problem with customizable city coordinates.
Detailed Documentation
This MATLAB source code provides an implementation of the Ant Colony Optimization (ACO) algorithm for solving the Traveling Salesman Problem (TSP). The algorithm simulates ant foraging behavior by modeling path selection and pheromone updates to find optimal travel routes. The code implementation includes key functions for distance calculation between cities, pheromone trail initialization and evaporation, probabilistic path selection based on pheromone concentrations, and route optimization through iterative improvements. Users can modify city coordinates in the configuration section to adapt the solution to different TSP scenarios. The algorithm utilizes heuristic information combined with pheromone trails to balance exploration and exploitation during the search process.
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