A hybrid heuristic algorithm for high-speed rail line planning problem with multiple transport organization modes

Abstract

This study investigated the line planning problem for high-speed rail (HSR) trains that must satisfy both passenger and freight transportation demand and operate in coordination on a common line. It is necessary to maximize the utilization of the transport capacity of the HSR network by applying multiple transport organization modes to simultaneously allocate passenger and freight demands and solve the operational schemes of passenger and freight trains in parallel. A multi-objective mixed integer linear programming (MO-MILP) model was constructed with individual HSR passenger and freight carriages as decision objects. To solve the NP-hard problem, a hybrid heuristic algorithm combining column generation and genetic algorithms was designed. The algorithm introduces strategies such as carriage candidate set, train formation and stops, and demand updating. The numerical experiment was based on real operation data of China's Dalian–Harbin HSR line and was compared with the existing solution method. The results indicate that the optimization effect of the line planning problem is remarkable.