Research On Location Of Bike-Sharing Distribution Center Considering Rebalancing

In recent years,with the development of science and technology and the improvement of living standard in our country,private cars have become a common means of transportation.Heavy traffic and poor air quality have seriously affected people’s normal life.In order to ease traffic pressure and reduce carbon emissions,bike-sharing came into being.As a new mode of transportation,Shared bikes provide a new way for residents to travel,adjust the urban traffic structure,and promote the sustainable development of urban traffic.However,with the development of bike-sharing,some problems in the bike-sharing system also appear correspondingly,such as "difficult to borrow a car,difficult to return a car" phenomenon,operators through the "rebalancing" process to minimize this phenomenon.So in this paper,on the basis of the traditional model of LRP,to share a bike as the research object,the process of "rebalancing" combined with a distribution center location problem to establish bike-sharing location-routing model of cycling characteristics,in the model considering the mathematical relationship between the demand of the parking bays,needs to use the positive and negative distinction between each take into and out of parking stations demand,so as to establish research model considering rebalancing of distribution center location problem.In this paper,the location problem of distribution center considering rebalancing is essentially a location routing problem.Location-routing problem is a NP-hard problem.Therefore,this paper uses the idea of genetic algorithm(GA)to solve the vehicle routing problem,and uses genetic algorithm(GA)to solve the location routing problem.In this paper,the chromosome coding method,selection operator,crossover operator and mutation operator are described in detail,and the effectiveness of the genetic algorithm(GA)designed in this paper is analyzed from the three aspects of the dispersion degree,calculation time and solution quality of the genetic algorithm(GA),which is verified The genetic algorithm in this paper has practical value.