Optimization Of Location Selection For Shared-Bikes Placement Points Considering Public Transportation Connections

With the implementation of the development strategy of a strong transportation country,green transportation is a promising way to promote the goal of "double carbon".Since its introduction,bicycle sharing has been well received and has attracted a large number of users due to its high degree of freedom,convenience and good fitness experience.The combination of bike-sharing and public transport is a solution to the "last mile" of the city,complementing the advantages of the two modes of transport,improving the accessibility of public transport and easing traffic congestion by connecting bike-sharing within a short distance.However,there has been little research into the rational planning and layout of bicycle sharing points,so it is of great theoretical and practical importance to consider the planning of bicycle sharing points and their connectivity with public transport.Given the above background,in order to meet the demand for sharing-bikes trips and improve the convenience of public transport connections,a model and algorithm for optimizing the location of sharing-bikes drop-off points is investigated.Drawing on the User Equilibrium Allocation(UE)model,the bike-sharing traffic is reallocated after each update of the siting plan.The objective function is established with the objective of minimizing user travel time and operating costs.The constraints are established by considering the public transport connection relationship,the number of drop-off points,the total number of drop-off points and the capacity of each parking point.Design an optimization model to solve the algorithm.A case study was carried out to analyse the accuracy and efficiency of the solution using the adaptive genetic algorithm(AGA)and enumeration method to optimize the solution based on the data of shared bicycle travel orders in Xiamen.The results show that the model and algorithm are able to obtain the approximate optimal solution for the optimal location of the drop-off point with fewer iterations,and the minimum error in the total operating cost of the system is only 4.4% and the total user travel time is 5%.In this case,operating costs were reduced by 12.9% and travel times by 14.26% before and after the optimization.It shows that the model and algorithm can solve the problems of confusing shared bicycle parking points and connecting public transport dilemmas,reduce travelers’ connecting costs,maximize travel convenience and improve the level of integrated connecting services.