Dynamic constraint and objective generation approach for real-time train rescheduling model under human-computer interaction

Abstract

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 rescheduling model that incorporates constraints and objectives generated through human-computer interaction. This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling. The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework. We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions. By summarizing rescheduling rules, we devise a rule-based conflict detection-resolution heuristic algorithm to effectively solve the formulated model. A series of numerical experiments are presented, demonstrating strong performance across the entire system. Furthermore, the flexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of human-computer interactions in the previous step. This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions. It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies.