Optimizing the route of logistics based on the hybrid ant colony algorithm

The ant colony algorithm (ACA) has been successfully applied to several combinatorial optimization problems, but it has some shortcomings such as its slow computing speed, and it is easy to fall into local optimal. So a hybrid ant colony algorithm is proposed to optimize the ACA parameters. Firstly, the basic feasible solutions are solved by ACA, and then the quadratic optimal results are gotten by mutation operators of GA. At last the optimal solution is obtained for the vehicle routing problem. The algorithm is applied to the logistical delivery routing problem. The simulation results show that its optimization quality and efficiency is superior to the traditional ACA and the GA.