Solving the bi-objective car-sharing problem including time-dependent user preferences
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
Operations Research 2019
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
The success of shared mobility systems largely depends on the users' satisfaction with the system. In the bi-objective multimodal car-sharing problem we aim at determining the optimal mode of transport (MOT) (car, bike, public transport and walking) for each sequence of user tasks, starting and ending at one of the depots, and to schedule the tours of available cars by concurrently minimizing cost and maximizing user satisfaction. The number of available cars is limited and they may be used by different users throughout the day.
We consider time-dependent user preferences for the different considered MOTs: users may choose and rank their preferred modes of transport for different times of the day. In this way we account for, e.g., different traffic conditions throughout the planning horizon. The underlying optimization problem is modeled in terms of a mixed integer linear program. Small instances can be solved to optimality by embedding the proposed model into the well-known epsilon-constraint scheme. For instances of realistic size, we employ advanced exact and heuristic search techniques. We compare several different variants of the problem (fixed and variable task sequences as well as fixed and time-dependent MOT-preferences) on a set of realistic instances; and we analyze the trade-off relationship between cost and user satisfaction.