A multi-objective and dictionary-based checking for efficient rescheduling trains

• Main Authors: Neeraj Kumar, Abhishek Mishra
• Format: Article
• Language: English
• Published: Elsevier 2021-06-01
• Series: Alexandria Engineering Journal
• Subjects: Multi-Choice Mixed Integer Goal Programming (MCMIGP); Gaussian Kernel Ant Colony Optimization (GKACO); Dictionary-based checking; Multi-objective function
• Online Access: http://www.sciencedirect.com/science/article/pii/S1110016821000302

In railway networks, unexpected disruptions happen for numerous reasons, which in-turn induce delays and cancellations that eventually bring about passenger inconvenience. Thus, the Trains Timetable Rescheduling (TTR) is required, but “how to reschedule the railway timetable” is an imperative issue in real train operations. Though the existing research works concentrated on rescheduling the timetable, the delay time along with reliability, still, are not greatly solved. Thus, this paper proposed a multi-objective and dictionary-based checking for effective rescheduling trains. In this proposed system, first, the constraints are extracted, and the MCMIGP metrics are illustrated. Next, the GKACO optimizes the constraints to make optimal rescheduling. In this algorithm, the multi-objective function is viewed as the fitness function, which is the amalgamation of minimization of a train delay, dwell time, timetable deviation, along with the operational cost and augmentation of service reliability. Subsequent to the generation of rescheduling, the rescheduled timetable's feasibility is checked based on the dictionary-based checking technique. If the rescheduled timetable is feasible, then it is denoted as the optimal timetable. Otherwise, the timetable is again rescheduled by using the same GKACO. Lastly, the experimentation's analysis proves the proposed TTR system's performance.