Calculating method of optimal path of data of traffic network

Abstract

According to the influence of traffic flow change on the selection of vehicle routing, to find a solution to the planning of travel routes in the situation that knowing the change of traffic flow. By using the method of particle swarm algorithm combined with dynamic programming to optimize the path of the vehicle, we can get the excellent route of each vehicle under the influence of the traffic flow. Simulating based on the road network structure and traffic data in real environment, the results showing that this method can increase the authenticity and dynamic of path optimization, and the road traffic flow and vehicle travel time having important influence on vehicle routing choice. Introduction Route planning of vehicle based on traffic flow makes the change of road network tend to diversity, authenticity. The optimization of path is not only to optimize the service order among customer points but also to optimize the route among the customer points based on the real environment. The target of optimization is from the shortest distance to the shortest time. In modern society time has gradually become the most important asset in people's live, the using efficiency of time becoming a prerequisite for pursuing maximum benefits of all walks of life. In the logistics industry, with the increase of the cost of logistics, how to timely and efficiently to complete the transport task has become an urgent problem of the logistics business enterprise to solve. Particle swarm optimization algorithm has merits of less number of individuals, simple operation, fast convergence speed, easy to realize, having been widely used by scholars in the field of computer science and management science, and having achieved many results. Wu Kaijun et al using binary particle swarm algorithm to optimize the vehicle routing, Zhang Liyan Zhang Wenjing proposed the application of particle swarm algorithm in the optimization of vehicle routing. In this paper, using particle swarm algorithm with the adaptive weight to optimize the initial of customer points and vehicle, optimizing the routine among the customer points phased according to the changes of the traffic flow of each road based on this, finally got the optimal route of distribution of delivery vehicles. Calculating method of optimal path of data of traffic network The problem of vehicle studied in this paper is vehicles to dispatch goods to customers successively. If the customer point is not scheduled to arrive at the destination, using the time penalty measures to deal with it. The objective function