Urban Rail Transit Rolling Stock Scheduling Optimization with Shared Depot

Abstract

This paper presents a coordinated model to optimize the rolling stock scheduling of two urban rail transit lines with a shared train depot. The proposed integrated and extended integrated optimization problems are transformed into mixed integer linear programming (MILP) problems, which can be efficiently solved by an ant colony optimization algorithm. Numerical examples based on the Beijing Subway System are implemented to demonstrate the performance of the proposed models and solution approach.