An Improved Ant Colony Algorithm and Its Application in Vehicle Routing Problem

Optimal path planning is an important issue in vehicle routing problem. This paper proposes a new vehicle routing path planning method which adds path weight matrix and save matrix. The method uses a new transition probability function adding the angle factor function and visibility function, while setting penalty function in a new pheromone updating model to improve the accuracy of the route searching. Finally, after each cycle, we use 3-opt method to update the optimal solution to optimize the path length. The results of comparison also confirm that this method is better than the traditional ant colony algorithm for vehicle routing path planning method. The result of computer simulation confirms that the method can plan a more rational rescue path focused on the real traffic situation.