Disruption Management at NS Crew scheduling using Multi Agent System techniques

Disruption management is an important topic in railway management and control. When a disruption occurs the original operational plan may become infeasible and will need to be revised to make it suitable for the new environment. The Dutch Railways (NS) address this problem and stress the importance of getting back to stable operations as efficiently as possible, especially in case of major incidents and disruptions. This research deals with a specific part of the problem, namely the planning of personnel on a newly generated train timetable. The current study employs Multi-Agent System (MAS) techniques, specifically Multiple Ant Colony Systems (MACS), to solve the scheduling problem. This research shows that MACS in itself is not enough to solve the scheduling problem, and heuristics are necessary to reach solutions of acceptable quality, which leads to the MACS algorithm. The experimental results obtained with the MACS algorithm were generated with the aid of a dataset supplied by the NS and subsequently compared to their best solution. Moreover, the results were also compared to a purely random choosing of tasks and a greedy algorithm. The quality of the NS solution was not equalled, but our system performed far better than random and greedy algorithms.