TY - JOUR
T1 - The service points’ location and capacity problem
AU - Raviv, Tal
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/8
Y1 - 2023/8
N2 - We study the design of a network of automatic parcel lockers to facilitate the last-mile delivery of small parcels where parcels are delivered via service points near their recipients’ home addresses. The recipients then pick up their parcels at convenient times. This method saves a substantial share of the handling and transportation costs associated with the parcel delivery process. The deployment of such a network requires decisions regarding the location and capacity of the service points. If a parcel has to be delivered through a service point with no remaining capacity, the parcel is sent directly to the recipient's address at a higher cost, or its delivery is postponed. Hence, there is a trade-off between the fixed setup cost, the variable operational cost, and the quality of the service. In this study, we take a bottom-up approach to the problem. We start by analyzing the dynamics of a single service point and show how to calculate a function that maps the parameters of its environment to the expected number of parcels that will be rejected from service or postponed. We then embed these functions in a mathematical model that optimizes the configuration of the network while considering the trade-offs described above.
AB - We study the design of a network of automatic parcel lockers to facilitate the last-mile delivery of small parcels where parcels are delivered via service points near their recipients’ home addresses. The recipients then pick up their parcels at convenient times. This method saves a substantial share of the handling and transportation costs associated with the parcel delivery process. The deployment of such a network requires decisions regarding the location and capacity of the service points. If a parcel has to be delivered through a service point with no remaining capacity, the parcel is sent directly to the recipient's address at a higher cost, or its delivery is postponed. Hence, there is a trade-off between the fixed setup cost, the variable operational cost, and the quality of the service. In this study, we take a bottom-up approach to the problem. We start by analyzing the dynamics of a single service point and show how to calculate a function that maps the parameters of its environment to the expected number of parcels that will be rejected from service or postponed. We then embed these functions in a mathematical model that optimizes the configuration of the network while considering the trade-offs described above.
KW - Facility location
KW - Parcel delivery
KW - Stochastic modeling
UR - http://www.scopus.com/inward/record.url?scp=85165230770&partnerID=8YFLogxK
U2 - 10.1016/j.tre.2023.103216
DO - 10.1016/j.tre.2023.103216
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AN - SCOPUS:85165230770
SN - 1366-5545
VL - 176
JO - Transportation Research Part E: Logistics and Transportation Review
JF - Transportation Research Part E: Logistics and Transportation Review
M1 - 103216
ER -