The rail-road Dial-a-Ride problem

Abstract

This paper addresses an original static Dial-A-Ride service designed for sparsely populated areas. The service relies on vehicles capable of switching between the road and an existing vacant railway network, which induces railway scheduling constraints that must be integrated into the solution algorithm. In the context of the static Dial-A-Ride Problem (DARP), a set of known users must be picked up and dropped off to desired locations while adhering to time windows at nodes and maximal riding time constraints. In our problem, there are additional constraints related to the vehicles when they operate on the rail, creating interdependencies between trips.We develop a generic solution method based on the Adaptive Large Neighbourhood Search (ALNS) framework, combined with a set covering approach to target DARPs with shared resource constraints and synchronization. The method is benchmarked on instances created from a specific region in France. The numerical results show the effectiveness of our approach in integrating resource constraints and the utility of using road-rail vehicles to maximize the number of users served.