Research on High-Speed Railway Timetable Rescheduling Based on Genetic Algorithm

Abstract

This paper presents an effective approach to address the challenge of rapidly restoring train operation order and automatically generating scheduling optimization schemes during abnormal events. The study focuses on high-speed railway, and establishes a high-speed railway train operation adjustment model, with the primary objective of minimizing the weighted total arrival delay time while satisfying various time and capacity constraints. To overcome the NP-hard nature of the problem, we propose a genetic algorithm approach with an appropriate coding mode, fitness function, crossover, and mutation rules. To validate the proposed model and algorithm, we use the operational data from the Beijing-Shanghai high-speed railway. The results of comparing the advantages and disadvantages of the genetic algorithm with the interval-only accelerated operation method demonstrate the feasibility and effectiveness of genetic algorithm, which can provide decision support for dispatching high-speed railway train operation scheduling.