Generation Method of Mixed Bus Fleet Scheduling Scheme Under Power and Energy Difference

Abstract:

In order to optimize the operation of the mixed bus fleet， a scheduling method that balances the environmental and economic costs of electric buses and fuel buses is proposed. Firstly， the constraints are given by combining the operation characteristics of buses with different power energy， and the carbon emissions and time-of-use electricity prices are integrated into the energy consumption and cost analysis of electric buses and fuel buses， then， considering the economic cost and environmental cost of the public transport system， a comprehensive operation cost minimization model is established， finally， an improved genetic algorithm with nested tabu search is used to solve the model. The algorithm not only compensates for the shortcomings of traditional genetic algorithms that converge prematurely and fall into local optimal solutions easily but also improves the quality and accuracy of the model solution. Bus No. 1 in Wenshan City， Yunnan Province， was taken as an example for verification. The results show that the improved genetic algorithm with nested tabu search improves the solution accuracy by about 12% compared with the traditional genetic algorithm， and the scheduling scheme generated achieves the best balance between reducing carbon emission costs and improving vehicle utilization and effectively reduces the overall operation cost. In addition， the scheduling scheme realizes the effect of electric bus task execution period and electricity price peak staggering and saves the charging cost， which provides a green， efficient， and reliable scheduling method for the smooth realization of the “electrification” of the bus fleet.

Key words:traffic planning;mixed bus fleet;intelligent bus scheduling;carbon emissions;taboo search genetic algorithm