Research On Multi-line Bus Scheduling Model And Algorithm For Mixed-type Vehicles

With the rapid growth of the economy,the number of motor vehicles is increasing drastically,leading to severe and the problem of traffic congestion.To address this,it’s essential to improve public transit vigorously,which can mitigate the congestion.Regular bus is an important part of public transport,and the operation of regular bus draws much attention recently.Vehicle scheduling is an important part of public transit operations,since an effective vehicle schedule can reduce costs for the bus company.However,the increasingly complicated operation environment brings up new problems for vehicle scheduling.On the one hand,due to the limited management capabilities of bus companies,previous works utilized single-line scheduling,which wastes vehicle resources to some extent.On the other hand,with a large number of pure electric buses put into use,bus vehicles have entered a period of upgrading.The fixed cost and running cost of pure electric vehicles are different from those of fuel vehicles,and the constraints in the operation process are also different.How to rationally use pure electric buses and existing fuel buses to reduce operating costs has also become a challenge for bus companies.To combat above challenges,this thesis proposes a multi-line vehicle scheduling for mixed-type vehicles,and the research contains several parts,as shown below.First of all,the thesis introduces the bus vehicle scheduling problem,summarizes the research results of the current bus vehicle scheduling problem by vehicle type,and elaborates on the electric energy constraint characteristics of pure electric buses and the carbon emission characteristics of fuel buses.Secondly,based on the research of common vehicle scheduling problem,combined with the characteristics of buses,a multi-line vehicle scheduling model for mixed-type vehicles is established.The model balances the environmental benefits and economic benefits,comprehensively considers the constraints of pure electric vehicles and fuel vehicles.While optimizing the bus vehicle schedule,the type of vehicle is also considered.Thirdly,according to the description of the problem and the characteristics of the established model,the coding scheme based on vehicle type and chains of trips is designed.On this basis,an improved genetic algorithm is designed to solve the multi-line vehicle scheduling problem for mixed-type vehicles.In addition,and an adaptive fitness function and an acceptance criterion of new solution are designed to prevent the algorithm from falling into a local optimal solution.Finally,the thesis selects six bus lines around Sihui transportation hub for example verification and analysis.The experimental results show that the multi-line bus vehicle schedule for mixed-type vehicles is better than the single-line or single-type bus vehicle schedule.In the multi-line mode,the operating cost is optimized by 0.22%-2.94%compared with the single-line mode,and the fleet size is reduced by 4.29%-5.56%.And the operating cost of the mode by mixed-type vehicles is optimized by 2.24%-15.43%compared with the single-type vehicle mode.In addition,the vehicle schedule of different price parameters and endurance mileage is analyzed to provide reference for the pure electric transformation of bus companies.