Based On The Robust Optimization Of Urban Rail Transit Elastic Departure Intervals

In recent years,the construction of urban rail transit system in China has become increasingly developed and sound.More and more residents take rail transit as their preferred mode of transportation when traveling,which often leads to the situation that passengers wait for a long time in rush hours and the carriages and platforms are crowded.At present,most urban rail transit operating enterprises cannot make profits and need to rely on government subsidies to maintain operations.Therefore,the biggest problem facing urban rail transit operating enterprises is how to provide passengers with higher quality services while ensuring their own profits.Based on the existing analysis of urban rail train scheduling research at home and abroad,found in the actual operation process,due to lines of OD traffic faced with uncertainty,the simulation prediction is difficult to deal with uncertain factors influence on traffic,how the line OD traffic uncertain flexibility to develop urban rail train departure intervals is the problem to be solved in this paper.Firstly,the temporal and spatial imbalance,fluctuation,periodicity and tidal characteristics of passenger flow of urban rail transit are analyzed in detail.The fluctuation range of OD passenger flow is determined.When the length of analysis period is 30 min,the overall OD passenger flow deviation of the line changes within 15% to 20%.This paper analyzes the influencing factors of urban rail transit scheduling,the related content of scheduling optimization and the advantage of elastic departure interval.It is proved that it is necessary to formulate elastic departure interval under the condition of uncertain passenger flow.Second,introduce know never deterministic robust optimization method,using the robust optimization method based on interval is established to minimize the passenger travel time and at the same time to maximize operating earnings at the peak of the elasticity of urban rail transit train departure interval optimization model,in order to more accurate expression of the uncertainty of OD traffic,limit traffic values in an interval.When transforming the model,rvalue is introduced to measure the conservatism of the model,and the maximum and minimum regret value method is chosen as the decision-making method.Finally,according to the selection of genetic simulated annealing algorithm to solve,and design the specific process,on this basis,using MATLAB to optimize the departure interval of Dalian Metro Line 1 peak period,through the minimum maximum regret value method to determine the optimal robust solution,compared with the original departure interval.It is found that the optimized elastic departure interval is more suitable for the change of passenger flow,and the actual data are used to test the scheduling plan,which shows that the departure interval formulated by the robust optimization has stronger stability,can better face the fluctuation of passenger flow,and verifies the effectiveness and superiority of the robust optimization.