An Improved Ant Colony Algorithm to Solve Vehicle Routing Problem with Time Windows

This paper presents an improved ant colony optimization algorithm (ACO algorithm) based on Ito differential equations, the proposed algorithm integrates the versatility of Ito thought with the accuracy of ACO algorithm in solving the vehicle routing problem (VRP), and it executes simultaneous move and wave process, and employs exercise ability to unify move and wave intensity. Move and wave operator rely on attractors and random perturbations to set the motion direction. In the experiment part, this improved algorithm is implemented for solving vehicle routing problem with soft time windows (VRPSTW), and tested by Solomon Benchmark standard test dataset, the result shows that the proposed algorithm is effective and feasible.