Dual-Population Ant Colony Optimization for TSP

The Dual-Population Ant Colony Algorithm for TSP is an optimization approach designed to solve the Traveling Salesman Problem. This implementation maintains two distinct ant populations that explore the solution space differently - one focusing on exploitation of known good paths while the other emphasizes exploration of new routes. The algorithm includes MATLAB data files: "30-city TSP problem data with optimal solution.mat" containing city coordinates and verified optimal path, "75-city TSP problem data.mat" with intermediate-scale test data, and "442-city TSP data with algorithm comparison.mat" which provides large-scale benchmarking data including performance comparisons with other TSP algorithms. These datasets support algorithm validation, parameter tuning, and comparative analysis through standardized test scenarios. Key implementation features include parallel path construction, dynamic pheromone update strategies, and population synchronization mechanisms to balance convergence speed and solution quality.