Research On Scheduling Management Optimization Method Of Public Bicycle System

As China's economy continues to develop at a rapid pace,the city continues to expand,causing a corresponding increase in vehicle ownership,and an associated rise in traffic congestion,environmental pollution,and energy consumption.The Chinese government has realized that excessive reliance on private car travel will lead to serious urban traffic congestion and environmental pollution problems,and has therefore put forward a strategy of “ prioritizing the development of public transportation ” and encouraging the city ' s multimodal transport development,including public bicycle systems.Public bicycle systems are not only an integral part of the urban transportation system,but also an important “last mile” connection method for city buses and rail transit.Combining public bicycles with other public transportation modes can lead more travelers to choose public transport,increase its attractiveness and competitiveness,lead to reduced urban traffic congestion and pollution,and promote the healthy development of the entire city's traffic system.However,the success of public bicycles in providing a reliable connection to other modes of transportation depends largely on the successful distribution of public bicycle rental sites and the efficient deployment of publ ic bicycles.This research about scheduling management optimization method aims to improve urban public transport mobility and accessibility,and solve the “last mile” problem.The purpose of this paper is to propose public bicycle scheduling optimization methods.a dynamic scheduling optimization method is considered.This work analyzes the variable factors of influence and impact on travelers ' willingness to choose the public bicycle system.Ordered logit and probit models were used to analyze the change in willingness to choose the bicycle system when improvements were made to the influential variables.The data used was collected from a random survey given in September and October 2014 in Nanjing city,China.The findings of this research show that there are seven factors that most influence users' willingness to choose the public bicycle system,including socioeconomic factors and journey restrictions.Socioeconomic factors(i.e.,gender,employment,and car ownership)have more impact on users' willingness than journey restrictions.In addition,the aforementioned socioeconomic variables,along with station facility consideration,have the greatest impact on increasing the probability of users giving the best choice willingness evaluation(“very willing”to use the system).The influencing factors related to the layout of public bicycle rental sites are also analyzed in this work.Based on these factors,this paper proposes a public bike rental site layout optimization method based on the mean square error TOPSIS method as the approach to finding the ideal point ranking method.Based on the rental site layout optimization.This paper proposes a two-stop method of dynamic division of public bicycle scheduling areas.Considering the location of public bicycle stations and the distance between stations using cluster analysis,the first step is to divide sites with similar distances into areas(i.e.,categories).Based on the first step,the second step is to balance the need of areas.This paper considers not only that the demand at public bicycle rental sites changes with time,but also considers the impact of uncertainties such as road blockage or weather changes on the speed of the vehicle redistributing the bicycles,and regards the optimization of public bicycle scheduling as a time-variant zone.In the scheduling path optimization time window problem,a mathematical model was established with minimum scheduling cost as the optimization goal.Based on the solution to this model,a path optimization algorithm based on time window difference detection insertion was proposed and verified.A multi-objective public bicycle dynamic scheduling optimization model with the lowest scheduling cost and the shortest scheduling distance is also established in this w ork,and a public bicycle scheduling optimization method is proposed.The method includes the generation of the optimal initial scheme and as well as the scheduling scheme 's dynamic adjustment.The method of generating the optimal initial scheduling scheme is based on a discrete differential evolution algorithm.This algorithm and the feasible neighborhood are used to find new mutations and crossover operators,and any infeasible solutions are effectively eliminated.Based on a global search using a discret e differential evolution hybrid algorithm,a local tabu search algorithm is then used to perform a local search for the optimal stations and a 2-opt feasible neighborhood structure is proposed.Using this neighborhood structure,infeasible stations are reduced,and an optimal initial scheduling scheme is obtained.Then,according to the demand forecast information and the real-time demand information,the optimal initial scheme is dynamically adjusted to adapt to the change in demand generated during the scheduling process,minimizing the scheduling cost and providing the shortest possible scheduling path.The scheduling optimization methods studied in this paper can provide theoretical support for public bicycle system planning and scheduling management,and have important research significance.The research results can be used to analyze the operation status of public bicycles,and can be used as a basis for the selection of public bicycle rental sites and formulation of dispatching strategies.