KEYWORDS: Education and training, Mathematical optimization, Bismuth, Transportation, Lithium, Chromium, Data modeling, Control systems, Computer programming, Algorithm development
In order to address the issue of passenger flow imbalance when metropolitan commuter trains cross-operate onto urban rail transit lines, this paper adopts a demand-driven approach. Optimization models are constructed with the goals of minimizing the waiting time for passengers on urban rail transit and minimizing the total travel time for passengers on the metropolitan line. An improved Harris Hawk algorithm is utilized for solving these models. To validate the effectiveness of the proposed models and algorithm, actual operational data from a specific metropolitan line and urban rail transit line are examined. The results indicate that by uniformly adjusting the departure intervals of both the metropolitan and urban rail transit trains, the objective function is reduced by 7.20%, the waiting time for passengers on the urban rail transit line is decreased by 4.96%, and the onboard travel time for metropolitan line passengers is reduced by 11.28%.
Due to the different purposes of passenger travel, the passenger flow has high instability in time. When designing the train diagram, it should not only meet the needs of passenger travel, but also highlight the carrying capacity during peak hours and holidays. Through the analysis of the temporal and spatial distribution characteristics of passenger flow and the characteristics of train diagram, the paper describes the balance scientifically. Through the study of the existing literature and the characteristics of passenger flow, this paper mainly establishes the equilibrium index system from three aspects: train, station and passenger flow matching degree. The fuzzy comprehensive evaluation method is selected to calculate the equilibrium value of the train diagram and evaluate its equilibrium.
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