Supporting the decision making process in the urban freight fleet composition problem

The Urban Freight Fleet Composition (UFFC) problem addresses the need of a logistics service provider to define the optimal fleet mix in terms of types and number of vehicles to serve the demand for goods delivery in an urban area. Urban areas can be subject to access restrictions (e.g. based upon the time of the day or vehicles’ characteristics) that could affect the performance of transport assets. In this paper, we consider time-window access restrictions based upon the characteristics of the vehicles, and we propose a human-in-the-loop decision support system (HIL-DSS) architecture using optimisation and simulation models to address the trade-off between vehicles characteristics, revenues, costs, and performance. We formulate both a deterministic and a stochastic optimisation decision model addressing the problem in the context of the HIL-DSS. In doing this, we emphasise the role of the human decision maker in tackling a complex problem affected by variability and uncertainty, and to overcome the rigidity of optimisation models thanks to the possibility to include qualitative information into the process.