Research on garbage truck path planning method based on improved ant colony algorithm Paper

Abstract

The current garbage truck path planning algorithm has the problems of not considering the capacity constraints, high computational complexity, and difficult to obtain the optimal solution. We propose a path planning method based on the improved ant colony algorithm. Firstly, this method adds the capacity constraint to the calculation process of the algorithm, and updates the capacity residual value when the ant explores. Then, by changing the update coefficient of the local pheromone to increase the pioneering of the algorithm, it is easy to obtain the optimal solution. By updating the global pheromone on the optimal path, it provides positive feedback and speeds up the optimization. Finally, the global pheromone is dynamically adjusted. This adjustment is to reduce the computational complexity, so that the algorithm can correct the iterative results in time and find the optimal path faster. Experiments show that the proposed algorithm can effectively solve the problem of collecting and transporting garbage trucks. It has the advantages of fast convergence speed and strong optimization ability of garbage truck path planning under capacity constraints. It is a feasible solution to garbage collection point garbage collection path planning method.