Collaborative Optimization of Passenger Control Strategy and Train Operation Plan with Variable Formations for a Rail Transit Network

We proposed a passenger control strategy and train operation plan collaborative optimization (PCS&TOP) model to schedule the that improves efficiency of passengers’ travel reduces cost for rail transit network. The is an integer non linear programming aims minimize entrance platform waiting time passengers trains. timetable variable formation are integrated optimized, turnaround rolling stock also considered by constructing constraints model. coordination timetables on different lines strategies at stations mentioned considering transfer when constraints. To solve model, multi-operator simulated annealing (MOSA) algorithm includes three types execution operators corresponding main decision variables proposed. A numerical case 2 bidirectional crossed real-world from China introduced test method, which demonstrates better performance than single respective solutions.