Design And Development Of WebGIS Transportation Distribution System Based On Genetic Algorithm

The booming development of the logistics industry provides a solid foundation for Chinese economic prosperity.However,with the concept of "smart logistics" being put forward,the logistics-oriented transformation of the logistics industry presents great challenges.Although transport capacity and delivery capacity of Chinese logistics industry have beening increasing year by year,its extensive resource allocation,low management level,and high cost have hampered the further development of the logistics industry,so the digitalization and informationization of the logistics industry is imminent.As one of the important links in the "closed loop of logistics",the transportation industry is very important to the logistics industry to upgrade,transform,integration,development of logistics methods.Therefore,how to use the existing computer technology and information technology to informatize,standardize and facilitate the traditional logistics industry,and propose a reliable and efficient transportation and distribution plan is urgent.Aiming at the transportation problems in the logistics industry,based on the analysis of domestic and foreign research statu,this paper designs a method for solving(non-)balanced transportation problems based on the combination of Monte Carlo similarity and genetic algorithm.Two coding methods are used: Prüfer number and matrix.On this basis,a dynamic mutation rate and a random mutation strategy are designed,and a Monte Carlo similarity receiving method is introduced.Finally,from the perspective of system requirements,a Web GIS transportation distribution system based on genetic algorithm was designed and developed.The main work and results of this paper are as follows:(1)Based on the review of domestic and foreign research status,the research background and significance of transportation problem in the logistics industry are introduced,and related theoretical knowledge such as genetic algorithms,Monte Carlo,similarity,and the front-end,back-end,database storage and Web GIS involved in system development are introduced;(2)The mathematical model and transformation relationship of balanced transportation problem and unbalanced transportation problem are introduced,and a genetic algorithm based on Monte Carlo similarity based on the above mathematical model is proposed.Based on the proposed algorithm,two coding methods,Prüfer number and matrix,are introduced;Dynamic mutation rate and random mutation strategies are used to enhance the algorithm's search ability and speed up the convergence rate;A Monte Carlo similarity receiving method is designed to avoid algorithm falling into local optimal solution.Finally,the algorithm is tested on the actual road network in Hangzhou.By the convergence speed,fitness,and average value of the optimal solution,the results show that the genetic algorithm,which adopts the matrix coding method and the monte carlo similarity operator,is more effective for solving the transportation problem;(3)After analyzing the information requirements,functional requirements,and performance requirements of the transportation and distribution system,designing the overall system architecture,system technical route,and overall system,and designing the database table relationships and table fields in detail.Based on the Arc GIS platform,combining the above algorithms,the front-end frameworks such as Vue.js,Bootstrap,and back-end framework technologies such as SSM are used to design and implement the transportation distribution system with the six functional modules including task list,task creation,OD cost,distribution scheme,task analysis,and personal center.Finally,the test results show that the system can effectively reduce distribution costs,increase corporate profits,and improve corporate efficiency.