Research And Implementation Of Bus Capacity Optimization And Intelligent Scheduling Method

Developing public transportation is an effective way to alleviate urban traffic congestion.The formulation of bus departure timetables and vehicle scheduling are key links in bus operations and directly affect the quality of bus services.However,the current methods lack consideration of the matching between bus capacity and passenger flow and the core constraints in the scheduling process,resulting in long waiting times,bus cannot be dispatched,and reduced attractiveness of bus services.In order to improve the quality of bus services,this paper studies the optimization of bus capacity and vehicle scheduling problems.Bus capacity optimization is the determination of the bus departure timetable,with the aim of meeting passenger flow demand through appropriate bus frequencies.Vehicle scheduling involves arranging vehicles to carry out the departure tasks in the timetable,ensuring that each time point in the timetable has a vehicle departure.A reasonable vehicle scheduling plan can save the number of vehicles used and reduce the costs of the bus company.The main contributions of this paper are summarized as follows:For the capacity optimization problem,a traversal search algorithmbased bus capacity optimization method is proposed,which can be used to solve the optimization problems of regular and branch-line bus routes.Firstly,the bus capacity provided by the bus company is matched with passenger demand through the capacity matching value,while considering the waiting time for passengers.Then,a consistent matching method for up and down time points is designed,considering the passenger supplydemand ratio,so that the total number of time points for vehicle departures in both directions is consistent,ensuring that there exists a feasible solution in which all vehicles perform an even number of trips and no empty loads.For the vehicle scheduling problem,a cultural genetic algorithmbased vehicle scheduling method is proposed,which can be used to solve the vehicle scheduling problems of regular and branch-line bus routes.Firstly,an initial population generation algorithm is designed,where each individual in the population represents a vehicle scheduling plan,and the generated initial population can satisfy all customized constraints for the timetable.Then,a local search algorithm is designed to improve the search capability of the algorithm,so as to obtain solutions that meet constraints such as the minimum rest time between shifts.An evaluation function is designed to guide the process of generating shifts,which increases the iteration efficiency and optimizes the quality of the solution.To verify the feasibility of the proposed method,actual passenger flow data from bus company routes were used to optimize the departure timetable and vehicle scheduling.The results were compared with manually designed plans and existing methods,demonstrating that the proposed bus capacity optimization and vehicle scheduling methods are superior to manual plans and existing methods.A bus capacity optimization and vehicle scheduling system was designed and implemented.The system meets the core requirements of bus capacity optimization and vehicle scheduling.Functional requirements analysis and non-functional requirements analysis were conducted,and the system was designed from four aspects:overall architecture design,functional module design,database design,and interface design.The system was designed in detail through class diagrams and sequence diagrams,and the system function was implemented and tested.