Ant Colony Algorithm + Dijkstra Algorithm = 2D Path Planning

The integration of Ant Colony Algorithm and Dijkstra Algorithm for 2D path planning represents a powerful combinatorial approach for solving real-world optimization problems. This hybrid algorithm effectively addresses various practical applications, including finding shortest paths in transportation networks and optimizing route planning in logistics systems. The implementation consists of MATLAB m-files organized with a main driver script that coordinates both algorithms sequentially. The Dijkstra component handles initial path exploration with guaranteed optimality, while the Ant Colony Optimization module refines solutions using pheromone-based swarm intelligence. Key functions include distance matrix calculation, path cost evaluation, and pheromone updating mechanisms. Users can simply download the package and run the main.m file to observe the path planning process through MATLAB's visualization interface, which displays both intermediate results and final optimized paths with clear cost metrics.