Research On Route Optimization Of Online Intercity Carpooling

With the development of economy and society,people are not only satisfied with the basic needs of accessibility when choosing travel modes.Convenience,comfort,safety and other factors have gradually become the most important factors for people to choose travel modes.Because of the inconvenience of traditional road passenger transport organization mode,road transport enterprises are facing enormous challenges of market loss and profit decline.Under this background,intercity network carpool came into being,through the mobile Internet platform,the relationship between supply and demand,integrating transportation resources under the line,give full play to the "door to door" advantage of highway transport.However,as a new mode of travel,there are still many unfavorable factors affecting its own development.How to solve these unfavorable factors is the key to the development of intercity network carpooling.It is also important for highway transport to stabilize the intercity travel market.This paper combines the research on vehicle routing problem at home and abroad,and carries out research on the optimization of carpooling routes on the inter-city network..This paper introduces the operation mode of intercity network carpool,and through sending questionnaires and mining the ordering data under the platform of inter-city carpool,analyses the demand characteristics and influencing factors of intercity carpool,and understands the individual travel characteristics and space-time characteristics of inter-city carpool.Principal Component Analysis(PCA)was used to analyze the questionnaire data and determine the weight of factors affecting the service level for intercity network carpool.Aiming at the factors affecting the service level for intercity network carpool,a multi-objective optimization model for intercity network carpool is established by referring to VRPPD problem,which minimizes the total mileage and the variance of passenger travel time.A hybrid genetic algorithm is designed to solve the optimization model of intercity network carpool.The fitness function of genetic algorithm is designed by using the weight of factors affecting demand.According to the characteristics of cross-city travel and the pairing of pick-up and drop-off points in the inter-city network,the coding form of genetic algorithm is designed.In order to overcome the shortcoming of the traditional genetic algorithm,which tends to fall into the local optimum prematurely and form "precocity",the simulated annealing Metroplis individual acceptance criterion was introduced into the crossover and mutation process of genetic algorithm,and the hybrid genetic operator was designed.The model and algorithm are validated by Python programming using passenger travel data of a Chengdu intercity network carpool platform.By comparing the changes of index values before and after optimization and the results of different algorithms,the feasibility and validity of the model and hybrid genetic algorithm are verified.