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.