Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and proces...Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.展开更多
Track utilization is the most important technical operation in high-speed railway stations.It is an effective way to take flexible man-agement based on dispatchers’decision preferences into consideration for making t...Track utilization is the most important technical operation in high-speed railway stations.It is an effective way to take flexible man-agement based on dispatchers’decision preferences into consideration for making track utilization plans to relieve the influence caused by unmeasurable unstructured factors.Thus,based on the flexible management concept and taking the flexible optimal for track utilization in high-speed railway stations as the object,time and space occupation safety trajectories of arrival routes,departure routes and tracks are all analysed.Then,taking the following constraints into consideration-minimum safety time intervals for var-ious routes and tracks occupation,space-time arc occupation and decision-makers’preferences-a flexible optimal model for track utilization in high-speed railway stations is established to maximize its balance and robustness and to minimize its volatility at the same time.Further,a flexible optimal solution based on a simulated annealing algorithm is designed to make a safety track utilization plan in high-speed railway stations integrating the dispatchers’decision preference.The results from the experiments show that the proposed methodology can effectively make satisfied safety track utilization plans based on decision-makers’preferences,which can improve its balance and robustness level significantly.Meanwhile,its volatility can be reduced as much as possible caused by flexible management based on artificial intervention to ensure the relative stability of the plan.展开更多
文摘Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.
基金This research is supported by the Natural Science Foundation of China(Grants No.71971220 and 71901093)Hunan Provincial Natural Science Foundation of China(Grants No.2023JJ30710 and 2022JJ31020).
文摘Track utilization is the most important technical operation in high-speed railway stations.It is an effective way to take flexible man-agement based on dispatchers’decision preferences into consideration for making track utilization plans to relieve the influence caused by unmeasurable unstructured factors.Thus,based on the flexible management concept and taking the flexible optimal for track utilization in high-speed railway stations as the object,time and space occupation safety trajectories of arrival routes,departure routes and tracks are all analysed.Then,taking the following constraints into consideration-minimum safety time intervals for var-ious routes and tracks occupation,space-time arc occupation and decision-makers’preferences-a flexible optimal model for track utilization in high-speed railway stations is established to maximize its balance and robustness and to minimize its volatility at the same time.Further,a flexible optimal solution based on a simulated annealing algorithm is designed to make a safety track utilization plan in high-speed railway stations integrating the dispatchers’decision preference.The results from the experiments show that the proposed methodology can effectively make satisfied safety track utilization plans based on decision-makers’preferences,which can improve its balance and robustness level significantly.Meanwhile,its volatility can be reduced as much as possible caused by flexible management based on artificial intervention to ensure the relative stability of the plan.
