The Research And Application Of Improved ITO Algorithm For Vehicle Routing Problem

Modern logistics industry is developing towards maximization, comprehensive and informazation. As the key part of logistics industry, vehicle routing problem will also become more complex, while traditional optimization algorithm in solving such a large and complex problem has the shortages of the slow convergence and local optimum. Therefore, the study of new algorithms has practical significance in solving vehicle routing problem and developing logistics industry.This paper proposes the improved ITO algorithm for solving vehicle routing problem with capacity constraints, which based on the deep analysis of vehicle routing problem and ITO algorithm. This paper also develops a distribution system according to the operation experience of the vending machine in practical applications. The main research works are as follows:(1) Analyzes the general characteristics of the swarm intelligence algorithms. Analyzes the basic principles, the key operator and the application of vehicle routing problem of ITO algorithm, ant colony algorithm and particle swarm optimization algorithm in contrast to illustrate the existing advantages of ITO algorithm.(2) According to the characteristics of gradual convergence of ITO algorithm in the iterative process and the particle in the actual movement process. This paper designs the path weight update rule combined with the wave operator and drift operator of algorithm. Introduces the economical method and combined with the path weight and distance heuristic factor to improve the client nodes selection rules of ITO algorithm. Designs the parameters of node selection probability formula dynamic change in iteration. By means of increasing the fluctuation coefficient and raising the temperature of the environment to avoid search stagnation and local optimum in the iterative process.(3) Uses the improved ITO algorithm to solve capacitated vehicle routing problem, which compares the simulation results of ITO algorithm with the results of other typical swarm intelligence algorithms. It proves that the improved ITO algorithm has a significantly better performance.(4) Develops a distribution system of vending machine and uses the improved ITO algorithm to plan the vehicle route. Develops the server platform of distribution system by means of Java. And it is applied to plan the vehicle route and monitor the operate information of vending machine in real-time. Develops the operating App based on Android. And it is applied to view the planned vehicle route and the working state of vending machines.