Inequity Averse Optimization of Railway Traffic Management Considering Passenger Route Choice and Gini Coefficient

Traffic management is crucial for improving the punctuality and reliability of train operations, enabling train operating companies to maintain their competitiveness and further increases the share and profits. We study the train rescheduling problem with the inclusion of passenger choices and the equity concerns. A mixed-integer linear programming (MILP) model is proposed to find the optimal train schedules and the best route for passengers at the same time, with respect to the demanded equity level. Passengers choose a sequence of train services to complete their trip with the least amount of costs (delays). To evaluate the equity performance of the system, we define equity by means of Gini Coefficient and Maximal Deviation, included in the MILP model as constraints.Experiments are conducted to explore the impacts of the objective change, i.e., from reducing train delays to reducing passenger delays, and to compare the system performance of using the two equity measures in terms of punctuality and equity. According to the results, the average passenger delay decreases by 34% when minimizing passenger delays, compared with that of minimizing train delays. Moreover, the Gini Coefficient yields less cost of equity (i.e., less increase of delays), compared to that of the Maximal Deviation