A Resource Allocation based Approach for Corporate Mobility as a Service

Corporate mobility is often based on fixed assignments of vehicles to employees. Relaxing these fixed assignments while including alternatives such as public transportation, bike sharing, and taxis for the employees' business and private trips could increase fleet utilization, foster the use of battery electric vehicles, and lower the costs for the companies' transportation needs. A system in which all employees specify their mobility demands gives rise to optimization problems concerning the assignment of company cars or alternative modes of transport to satisfy the needs of the users. In this work we introduce the NP-hard mobility offer allocation problem which has similarities to interval scheduling problems. We propose an integer linear programming model and heuristic solution approaches based on large neighborhood search. The efficiency of these methods is based on the usage of suitable conflict graphs. In a computational study, the approaches are evaluated and it is demonstrated that, depending on instances and run-time requirements, either solving the model exactly using a general purpose integer linear programming solver, fast greedy heuristics, or the adaptive large neighborhood search outperforms the others.