Research On Key Technology Of Commercial Vehicle Transportation Integrated System

With the continuous improvement of living standard,the demand for commercial vehicle is increasing.Road transport has become the main mode of commercial vehicle,but it has long transport time and much unpredictable risks.Therefore,informational management and supervision of large logistics road transportation is an important guarantee to improve the transport capacity and safety of logistics enterprises.To this end,the thesis designs the framework of commercial vehicle transportation integrated system on the background of an international logistics enterprise,and the system is implemented combining the research on vehicle scheduling optimization and logistics customer segmentation technology.The main research contents of this paper are as follows:(1)The demand of large logistics transportation integrated system is analyzed with the investigation of an international logistics enterprise.The overall design framework and main functions of the system are introduced,and the key technologies of the system are elaborated.(2)A multi-objective vehicle scheduling model with two-dimensional loading constraints is designed and a vehicle scheduling optimization algorithm is proposed aimed at the characteristics of vehicle scheduling constraints in the commercial vehicle transportation integrated system.An improved minimum horizontal line search algorithm is designed by using the heuristic rules to improve the vehicle reloading rate.A heuristic factor of time width is designed,a pseudorandom probability rule is introduced,and the minimum threshold for the update of the ant pheromone,which improves the search ability and performance of multi-objective ant colony optimization algorithm.The experimental results and practical applications in the system show that the algorithm has a good solution for multi-objective vehicle scheduling problem and meets the real-time and stability requirements of the system.(3)A logistics customer segmentation method based on sparse fuzzy clustering is proposed for the poor effect of customer management in the system.The original data is de-noised and normalized with the construction of logistics customer value system in the phase of logistics data preprocessing.The sparse clustering method id introduced to improve the quality and stability of the FCM clustering algorithm.The algorithm can subdivide the logistics customers effectively and provide the reliability basis for the decision of the enterprise.(4)The application background of commercial vehicle transportation integrated system is introduced.The main functions of the system are implemented.The implementation details of two key technologies,which are vehicle scheduling optimization and logistics customer segmentation,are elaborated and good performance is demonstrated.