Late Train-Crew Rescheduling—a Model and a Heuristic Approach

In this paper, we reschedule the duties of train drivers one day before the operation. Due to absent drivers (e.g., because of sick leave), some trains have no driver. Thus, duties on the operation day need to be rescheduled. We start with a feasible crew schedule of the remaining operating drivers, a set of unassigned tasks which were assigned to the absent drivers, and a group of standby drivers with fixed start time, end time, start depot, and end depot. Our aim is to generate a crew schedule with as few cancelled driving tasks and changed tasks as possible. We developed a Mixed Integer Linear Programming (MILP) model for short-term crew rescheduling. We also present a Tabu-Search-Based approach with the same objective function and equivalent restrictions of our mathematical model. We compare the results of the MILP model solved by Gurobi 11.0 and of the Tabu-Search-Based approach. Our Tabu-Search-Based approach takes less time and memory occupation to compute a ‘good-enough’ result. We further test the performance of our approach under different circumstances. The data used in the experiments are real data provided by Mälartåg.