A new urban freight distribution scheme and an optimization methodology for reducing its overall cost

Abstract

Purpose The paper refers to an innovative urban freight distribution scheme, aimed at reducing the externalities connected with the freight delivery process. Both packages destined to commercial activities and to end consumers (e-commerce) are taken into account. Each package is characterized by an address and dimensions. In the proposed transport system, freight is firstly delivered to the UDC on the border of urban areas through trucks or trains which perform the long distance transport. After, freight is reorganized and consolidated into load units, i.e. the FURBOT boxes, according to packages dimensions and to the addresses of receivers. Each box is addressed to a temporary unloading bay and it is delivered there by a FURBOT vehicle. The receivers are in charge of collecting their packages in the related unloading bays where they have been delivered. Methods and results The paper concerns a methodology for optimizing this freight transport system's performances. The overall methodology receives in input the actual freight demand and the road network, and finds the transport system parameters (number of required FURBOT boxes, their temporary unloading bay, the FURBOT fleet dimension and the FURBOT vehicle routing) that minimize the system overall cost. The overall cost is a sum of the users' cost, which depends on the distance they have to walk for collecting their packages in the FURBOT box, and of the operator's cost, which depends on the number of required boxes, the total distance travelled by the FURBOT vehicles and the required number of FURBOT vehicles. Application The overall procedure has been applied to the case study of Barreiro old town, a suburb of Lisbon, Portugal.

Collaborative urban transportation: Recent advances in theory and practice

“…As shown in Rose et al (2017), urban areas are characterized by the interplay of different stakeholder interest in close quarters, and, as highlighted in Kin et al (2017), megacities add growing sustainability challenges. Further obstacles include low load factors, empty trips, long dwell times at loading and unloading points, and large numbers of deliveries to individual customers (Cepolina and Farina, 2015). The key challenge for the future is rethinking the way existing infrastructure is used and how new infrastructure is built, so that it is fully utilized and negative externalities are minimized.…”

“…There are many studies on the impact of vertical collaboration on urban logistics practice that do not necessarily address OR models. Cepolina and Farina (2015) consider the transport of standardized load units ("FURBOT boxes") and discuss alternatives such as pack stations and bento boxes. The FURBOT system supports the consolidation of packages with multiple destinations into a single unit with multiple, lockable doors, ensuring the security of the freight en route to its destination.…”

“…To the best of our knowledge, existing models in an urban context do not consider collaborative settings (e.g., in location routing (Nagy and Salhi, 2007)). In some problem settings, existing models may be applicable, such as when passengers and freight exclusively share light rail infrastructure and when UCC locations are given in advance (e.g., Cepolina and Farina (2015)). This would also encourage more inter-modal transport on the last mile, as argued for long-distance transport in Colicchia et al (2017).…”

Hospital-wide therapist scheduling and routing: Exact and heuristic methods

“…The results have demonstrated that the cutting plane algorithm for scheduling therapy jobs and routing therapists hospital-wide can substantially reduce solution times. We argue that the approaches can be generalized for solving other problem instances in other service industries such as parcel delivery in which delivery locations are flexible (Cepolina and Farina (2015)).…”

Freight distribution in urban areas: a method to select the most important loading and unloading areas and a survey tool to investigate related demand patterns

“…Cluster analysis can help in this case, since it is a technique aiming at finding collections of objects such that the elements in a group will be similar (or related) to one another and different from (or unrelated to) the elements in other groups [25]. Examples of exploitation of this data mining methodology can be found in different domains of transport engineering such as transit quality evaluation [26] or tours classification [27], while its use in urban logistics can be exploited for the organization of deliveries according to city's characteristics [28] or the optimization of freight transport system's performances [29].…”