Abstract: In view of the current situation that the predominant method of railway survey vehicle scheduling is that the driver responds to the surveyors to realize picking and sending, which leads to a long waiting time. A study is conducted on how to build a reasonable vehicle scheduling optimization model to realize the balance and collaborative optimization of workload distribution and to generalize survey cost for the sake of providing the optimal transportation organization guarantee for the survey work. According to the traveling characteristics of survey vehicles, the extended network of picking and sending is used to describe the optimization problem of survey vehicle scheduling. On this basis, the bi-level programming model of vehicle scheduling is established considering the interests of decision makers and drivers. The upper model ensures the most balanced distribution of generalized survey cost, and the lower one solves the multi-vehicle routing model with picking and sending. The case study shows that the generalized survey cost based on the bi-level programming model of survey vehicle scheduling is reduced by 18.0% compared with the current reactive scheduling method, which verifies the effectiveness of the model and algorithm.

Key words: railway survey, vehicle scheduling, bi-level programming, genetic algorithm