Train scheduling method based on urban rail transit train timetable peak transfer optimization

Abstract

The invention discloses a train scheduling method based on urban rail transit train timetable peak transfer optimization. The train scheduling method comprises the following steps: 1, defining a group of peak transfer coefficients and determining each time input parameter; 2, initializing a peak conversion coefficient, and connecting branch time tables of the off-peak time period and the peak time period according to each time input parameter to obtain an initial train number time table and a train number set; 3, initializing enough trains, enabling the trains to completely cover the train number set based on a discrete event simulation method, and obtaining the minimum number of trains executing train number tasks; and 4, optimizing the peak conversion coefficient by using a simulated annealing algorithm to obtain a corresponding optimal train scheduling scheme under the optimal peak conversion coefficient. According to the method, the problem of train timetable connection when the off-peak period is converted into the peak period and the peak period is converted into the off-peak period can be solved, the existing fragmented timetable compiling problem is solved, and an efficient train scheduling scheme is obtained, so that the vehicle utilization rate can be improved, and the compiling efficiency and quality of a working diagram can be improved.

Description

technical field [0001] The invention relates to train dispatching optimized for peak shifting of urban rail transit timetables, belonging to the technical field of urban rail transit intelligence, in particular to a train dispatching method based on peak shifting optimization of urban rail transit train timetables. Background technique [0002] With the rapid development of urban rail transit, the road network structure is becoming more and more complex, and the passenger flow is increasing. Train timetable is the basis of urban rail transit operation organization. A reasonable timetable scheme requires that the transportation capacity should match the passenger flow, and trains should be dispatched efficiently to meet the needs of transporting passenger flow. Therefore, in considering the problem of train timetable preparation due to the influence of passenger flow, in order to effectively connect the sub-schedule timetables between flat peak hours and peak hours, optimize ...

AI Technical Summary

Problems solved by technology

Based on the mathematical model method, the model establishment is relatively easy, but the corresponding solution design is difficult and the calculation amount is large, and the calculation takes a long time

The simulation method based on discrete events can carefully describe the running state of the train, reduce the amount of calculation, and obtain the solution of the problem in a very short time, but the accuracy of the solution still needs to be further improved

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