A change in bus fare influences passenger choice behavior, resulting in a change of passenger flow and passengers’ total travel time. In this paper, a bi-level model was built to optimize the bus fare. The upper-level used the passenger flow and the travel time of passengers to optimize the bus fare. The lower-level is an agent-based simulation model that can simulate the passenger flow based on the passenger choice behavior. Then the tabu search algorithm was used to solve the bi-level model. Finally, the bi-level model is verified using two bus routes of Dalian, China. The result proves the bi-level model is reliable.
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