Optimal Planning for the Double-Track Train Scheduling Based on Chaotic Particle Swarm Optimization

Abstract

This paper proposes a multi-objective optimization model for the double-track train scheduling optimal planning problem. In this study, lowering the fuel consumption cost is the measure of satisfaction of the railway company and shortening the total passenger-time is being regarded as the passenger satisfaction criterion. To overcome the drawbacks of conventional mathematical optimization method in arriving at local optimum and dimension disasters, etc., we introduce the chaotic particle swarm optimization (CPSO) technique into the train scheduling for double-track railroad planning for the first time, from which the supreme scheme is generated. A case on the train scheduling optimal planning problem is presented to illustrate the methodology’s feasibility and efficiency, compared with the existing optimal planning methods, the search time of the particle swarm optimization method is shorter.