Research on Logistics allocation path Optimization in E-business Based on Ant Colony Algorithm

Logistics distribution is one of the most critical links of e-business, but its path optimization has been proved to be a NP hard problem. Traditional logistics distribution decisions mostly adopt centralized decision-making methods or some simplified algorithms, such as discrete optimization algorithm and heuristic algorithm. They can only solve local problems, and it is difficult to achieve optimization under global control. Moreover, some algorithms are only suitable for specific occasions, It is difficult to guarantee the validity of its solution. Using the well-known relativity between traveling salesman problem and ant colony search food process, the traveling salesman problem is solved according to the artificial simulation of ant search food process. At present, many ant colony algorithm problems have been successfully used in traveling salesman problem. In this paper, aiming at the optimization path problem of e-business logistics distribution, the ant colony algorithm is improved to improve its searching ability and speed up the convergence. Through simulation, it is proved that this method is feasible and effective in solving the optimal path of e-business logistics distribution.