Analysing different operational Scenarios for the Dial-a-Ride Problem

The Dial-a-Ride Problem (DARP) aims to find a set of minimal cost tours for a heterogeneous fleet of vehicles in order to satisfy a set of transport requests. Further restrictions, namely customer chosen time window sizes, pick-up and drop-off locations, and capacity constraints are generally customary. A common example arises in door-to-door transportation of people, especially elderly people or people with impaired mobility. In this work, we consider a dynamic-deterministic variant of the DARP for two Austrian mobility providers that focus on rural regions. As additional conditions, we take the transportation of people with impaired mobility, break times, and the capacity of wheelchairs into account. We consider a heuristically and an exact solution approach, namely a Large Neighborhood Search and a Mixed-Integer Linear Programming approach. In a computational study, we show different operator scenarios including minimizing overall driven kilometers, number of used vehicles, and number of unscheduled requests.