Train planning optimization for through operation of urban rail transit considering load balance

Abstract:

To optimize the train planning for through operation of urban rail transit, the operation organization method of through operation was analyzed, the passenger flows under through operation mode were classified, and a method of calculating the imbalance coefficient of the maximum load was proposed. A train planning optimization model for the through operation of urban rail transit was established by considering multi-group train operations and the imbalance of the load factor. The objective of this model was to minimize the travel cost of passengers, the operation cost of enterprises, and the imbalance coefficient of the load factor. Three decision variables, the location of turn-back stations, the frequency of different routing trains, and the formation of train groups, were solved by a hybrid coding genetic algorithm. Taking the Beijing Metro Fangshan Line and Line 9 as an example, the train planning optimizations for peak and off-peak hours were studied. The operational indicators such as load factors under through operation mode and independent operation mode were compared and analyzed. The effects of different objective weights on the optimal solution and optimization results were investigated. Results showed that during peak hours, compared with the independent operation mode, the optimization effect of the through operation mode was improved by 12.85% without changing the train formation plan. During off-peak hours, the multi-group train operation significantly improved the balance of the load factor. Through weight analysis, it was found that with the decrease in passenger service level weight and the increase in operating enterprise cost weight, the frequency of through trains decreased, the section of through operation gradually declined, and the effect of through operation steadily deteriorated.