Design And Implementation Of Vehicle Scheduling Optimization Algorithm For Intelligent Logistics Platform Based On Hadoop

With the rapid development of the global economy,the logistics industry has gradually become the foundation and main industry of the social and economic development,and its progress can be regarded as an indicator of whether the social economy can be modernized or not.However,at present,China's research on logistics and distribution services is still in the stage of studying traditional logistics problems.In recent years,due to the rapid development of e-commerce and the rapid growth of online shopping on the Internet,there have been great changes in the way of logistics distribution.The new forms of distribution,such as large-scale distribution and dynamic distribution,have come into being.The traditional logistics and distribution service can not maintain the demand of modern customers,and it does not conform to the increasing complexity.Supply chain system,to ensure the rapid and regular supply of goods and stable supply system,the realization of the distribution of logistics and the time of time,has been the key problem that the domestic logistics industry has to face.Especially after the emergence of cloud computing technology and communication technology,the dynamic distribution needs of large and multi regions can be realized,and the new form of logistics distribution will soon appear.This article uses the popular cloud technology in recent years and the old logistics management methods to integrate,set up the cloud logistics management platform,which is of great help to the slow development of the logistics industry.The cloud platform receives the requirement of distribution,so that many logistics enterprises in the social field are involved in the system,assemble mass logistics freight list,build a large-scale cloud computing platform,unify the mass data,and make the optimal scheduling scheme through the logistics distribution center of various domestic enterprises.First,Hadoop technology is introduced.It includes Hadoop platform and platform technology,and explains the background of Hadoop technology,andintroduces two important modules of Hadoop,which are the parallel operation framework of HDFS and MapReduce,at the same time,the storage and data model of Hadoop's sub project HBase system are also studied and analyzed.Then,according to the requirements of the scheduling,the cloud logistics platform scheduling system is designed,including the overall framework,that is,the data layer,the storage layer and the scheduling algorithm layer and so on.Secondly,for dynamic demand scheduling problem,because dynamic demand scheduling problem is evolved through static problem,dynamic problem is discussed and dynamic vehicle problems are influenced by information change reasons.Therefore,using time axis and dynamic information form a combination of information to produce information in the process of network distribution.The dynamic vehicle scheduling problem is converted into a number of static vehicle scheduling problems,and the constraints and target functions are considered as the reasons.The mathematical model of vehicle scheduling with specific time nodes is constructed.In order to solve the dynamic requirement of vehicle routing problem,the algorithm has the characteristics of high timeliness,which is based on the improvement of traditional genetic algorithm to form a quantum genetic improvement calculation.The quantum genetic diversity is used to carry out the chromosome coding,and the evolution process is realized through the rotation of the quantum gate,and the design algorithm is fused with the MapReduce programming model.In order to improve the efficiency of population evolution and design phase solving strategy by vehicle scheduling model,the time point is used to record the time point by the time axis concept,and the optimization operation process can be realized by using the time axis concept.Taking the smart city logistics platform as an experimental project,the paper verified the excellent performance of the design model and algorithm through experiments.In the last chapter,we summarize the contents of the paper,and look forward to the research trend of cloud computing logistics platform's operation mode and vehicle routing scheduling plan.