Intelligent Vehicle Scheduling Model Research And Application In Logistic Distribution

With the continuous development of market economy, enterprise informatization becomes more and more important. Logistics, taken as"third profit resource", has been great attention and developing rapidly. The basic feature of modern logistics is that computer network, e-commerce technical and logistics are combined to achieve the sharing and networking of logistics information. Lots of distribution centers that are taken as core business are established to improve the efficiency of goods flow and market response by large factories and enterprise.This paper attempts to research technologies in all aspects of logistics and combine computer software with logistics to provide effective solutions. This paper takes as vehicle scheduling and delivery routing as the core problem. This paper research includes the following aspects:(1) This paper analyzes the basic problems of vehicle scheduling and establishes vehicle scheduling mathematics model. According to different the vehicles'charging capacity, the problem is divided into full operation scheduling model and non-full. We solve two different vehicle scheduling model by two different algorithms and apply the model to logistics distribution system.(2) We solve non-full vehicle scheduling model by genetic algorithm and research the basic principles of selection, crossover and mutation in genetic algorithm. Improving the chromosome encoding scheme can improve the efficiency of genetic algorithm and simplify the operation of genetic operators. When vehicle scheduling with time window constraining is solved, the penalty function is introduced to objective function.(3) On the fully loaded vehicle scheduling model problem, the vehicle route is a point-to-point of delivery routes that is a typical shortest path problem. This paper solves this mathematics model by Dijkstra algorithm. In traditional Dijkstra algorithm, some problem occurs. We also present methods of improving the algorithm and optimization strategy.(4) On the multiple source vehicle scheduling problems, we partition the customer delivery points into several zones and each one correspond to a distribution point. So, this problem is transform into a single source vehicle scheduling problem.Finally, according to actual situation, the vehicle scheduling model is applied to logistics distribution system. It is shown the effectiveness and feasibility of model by example. So, vehicle scheduling become more and more intelligent and save logistics cost and reduce vehicle consumption and increase the efficiency of logistics.