Train timetabling with stop-skipping, passenger flow, and platform choice considerations

In conventional railway planning processes, stop-skipping decisions are often made at the line planning stage, which is executed prior to train timetabling and platform assignment. However, stop-skipping can shorten passenger journey time and also save on train operating costs. Hence, integrating train timetabling, stop-skipping, and platform choice decisions can help generate train timetables with improved passenger convenience and higher train operating efficiency. Integrating these decisions is a challenging task, as these decisions affect passenger train transfer behavior, which in turn affects the entire passenger flow. This study is a first attempt at integrating these decisions while simultaneously taking into account the passenger flow. We consider a train timetabling problem on a single, one-way track with stop-skipping, platform choice, and passenger flow considerations, and we formulate it as a constrained minimum-cost multi-commodity network flow problem on a time–space network. We analyze the problem's complexity and develop a Lagrangian relaxation heuristic to solve the problem. We conduct a computational study with randomly generated data that captures the characteristics of the Beijing–Shanghai high-speed railway line. The computational results report the effectiveness of our Lagrangian relaxation heuristic and how the railway's service capacity and passenger traffic intensity affect the solution.