The Research On Optimizing Route Of Logistics Based On Improved Hybrid Ant Colony Algorithm

With the rapid development of economy and science and technology,online shopping has gradually become a popular trend.This phenomenon led to the rapid development of the logistics industry,then the establishment of rationalization of the logistics and distribution system has become a top priority.Among them,one of the most critical part is the distribution of vehicle routing optimization.Logistics distribution is essentially a path optimization problem,belonging to the NP problem.The continuous expansion of the problem makes the traditional algorithm can not calculate the optimal solution in a finite time,so it is inspired by the bionics,and many heuristic optimization algorithms are proposed.This provides a new way to solve the difficult path optimization problem.Ant colony algorithm is a heuristic algorithm for simulating the foraging behavior of natural ants,and has achieved good results in solving various combinations of vehicle routing optimization(VRP)and traveling salesman problem(TSP).However,the traditional ant colony algorithm has the advantages of long searching time and easy to fall into the local optimal solution.In view of the above problems,this paper introduces some genetic operators in the ant colony algorithm,and makes the improvement in the realization process.In this paper,we first establish a mathematical model with constraints on the logistics distribution path optimization problem,and then let the ants start from the distribution center at the same time,and the number of cycles to group.Group to achieve search and copy,group outside the mutation,comparison and update pheromone.The purpose of updating the pheromone outside the group is to increase the pheromone concentration on the optimal solution path and to speed up the next set of ant searches for the optimal solution.