Crowd-shipping is a new delivery paradigm that is gaining success in the last-mile and same-day delivery process. In crowd-shipping the deliveries are carried out by both regular company vehicles and some crowd-drivers, named occasional drivers (ODs). ODs are ordinary people available to make deliveries, for a small compensation. We consider a setting in which a company not only has ODs available to make deliveries, but they may also use the services of intermediate pickup and delivery points, named occasional depots. In order to optimize the use of these depots, we consider two distinct groups of ODs with different operative ranges. Occasional depots are activated only if it is necessary or convenient; hence, their activation implies an "activation cost". These depots should increase the flexibility of the system and they lead to a more efficient managing of the uncertain availability of ODs. In this work we present a mixed integer linear programming model to represent this framework. We carry out computational experiments to validate it on small size instances.
Crowd-Shipping and Occasional Depots in the Last Mile Delivery
Di Puglia Pugliese L;
2021
Abstract
Crowd-shipping is a new delivery paradigm that is gaining success in the last-mile and same-day delivery process. In crowd-shipping the deliveries are carried out by both regular company vehicles and some crowd-drivers, named occasional drivers (ODs). ODs are ordinary people available to make deliveries, for a small compensation. We consider a setting in which a company not only has ODs available to make deliveries, but they may also use the services of intermediate pickup and delivery points, named occasional depots. In order to optimize the use of these depots, we consider two distinct groups of ODs with different operative ranges. Occasional depots are activated only if it is necessary or convenient; hence, their activation implies an "activation cost". These depots should increase the flexibility of the system and they lead to a more efficient managing of the uncertain availability of ODs. In this work we present a mixed integer linear programming model to represent this framework. We carry out computational experiments to validate it on small size instances.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.