Adaptive rescheduling of rail transit services with short-turnings under disruptions via a multi-agent deep reinforcement learning approach
This paper presents a novel multi-agent deep reinforcement learning (MADRL) approach for
real-time rescheduling of rail transit services with short-turnings during a complete track …
real-time rescheduling of rail transit services with short-turnings during a complete track …
Passenger service-oriented timetable rescheduling for large-scale disruptions in a railway network: A heuristic-based alternating direction method of multipliers
Unpredictable disruptions arising in railway operations can cause significant inconvenience
for passengers, including missed connections or deviations from their travel plans. To …
for passengers, including missed connections or deviations from their travel plans. To …
[HTML][HTML] Dynamic constraint and objective generation approach for real-time train rescheduling model under human-computer interaction
Real-time train rescheduling plays a vital role in railway transportation as it is crucial for
maintaining punctuality and reliability in rail operations. In this paper, we propose a …
maintaining punctuality and reliability in rail operations. In this paper, we propose a …
A 0, 1 Linear Programming Approach to Deadlock Detection and Management in Railways
V Dal Sasso, L Lamorgese, C Mannino… - Transportation …, 2024 - pubsonline.informs.org
In railway systems, a deadlock occurs when trains accidentally occupy positions that prevent
each other from moving forward. Although deadlocks are rare events, they do occur from …
each other from moving forward. Although deadlocks are rare events, they do occur from …
[HTML][HTML] A MaxSAT approach for solving a new Dynamic Discretization Discovery model for train rescheduling problems
Train scheduling is a critical activity in rail traffic management, both off-line (timetabling) and
on-line (dispatching). Time-Indexed formulations for scheduling problems are stronger than …
on-line (dispatching). Time-Indexed formulations for scheduling problems are stronger than …