Study on optimization of bus scheduling
DOI:
https://doi.org/10.54097/fcis.v1i1.1465Keywords:
Passenger flow big data, Passenger flow forecast, Bus scheduling, Genetic algorithmAbstract
In order to respond to the national policy, energy saving and emission reduction, from the perspective of transportation, we should drive fewer private cars and take more buses and subways. Good bus scheduling can better meet the interests of passengers and bus companies. Through the analysis of passenger flow big data, a more reasonable scheduling scheme can be provided for bus operation. The optimization of bus scheduling can improve the service quality and benefit passengers, and also reduce the input cost of bus companies. This paper analyzes the existing public transportation scheduling problems, analyzes the current research results of public transportation scheduling, and finally makes a prospect for public transportation scheduling.
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References
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