Integrated optimization of train timetable, rolling stock assignment and short-turning strategy for a metro line

Abstract

In many large cities, metro operations during peak hours are characterized by an overcrowded and unevenly-distributed passenger demand. This paper introduces a new integrated optimization model for the train timetable, rolling stock assignment, and short-turning strategy on a bidirectional metro line. The purpose is to increase the number of services in higher-passenger-demand segments using limited trains, thereby reducing passengers’ total waiting time on platforms. In particular, we simultaneously consider the multiple service operation zones, the train capacity, the turnaround operations, and the number of available trains. To obtain high-quality solutions, we develop a hybrid algorithm that combines a genetic algorithm with a general-purpose solver. Two sets of case studies, with a simplified metro line and the Beijing metro line 6, are implemented to verify the effectiveness and efficiency of the proposed hybrid algorithm.