  Recent developments in modular transport vehicles allow deploying
multi-purpose vehicles which can alternately transport different kinds of
flows. In this study, we propose a novel variant of the pickup and delivery
problem, the multi-purpose pickup and delivery problem, where multi-purpose
vehicles are assigned to serve a multi-commodity flow. We solve a series of use
case scenarios using an exact optimization algorithm and an adaptive large
neighborhood search algorithm. We compare the performance of a multi-purpose
vehicle fleet to a mixed single-use vehicle fleet. Our findings suggest that
total costs can be reduced by an average of 13% when multi-purpose vehicles are
deployed, while at the same time reducing the total vehicle trip duration and
total distance travelled by an average of 33% and 16%, respectively. The size
of the fleet can be reduced by an average of 35%. The results can be used by
practitioners and policymakers to decide on whether the combination of
passenger and freight demand flows with multi-purpose vehicles in a given
system will yield benefits compared to existing fleet configurations.
