The service points’ location and capacity problem
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 shar...
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Veröffentlicht in: | Transportation research. Part E, Logistics and transportation review Logistics and transportation review, 2023-08, Vol.176, p.103216, Article 103216 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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.
•Characterizing the rejection and postponement in a parcel delivery service point.•Designing a network of automated parcel delivery service points.•Presenting a mathematical model that integrates the above characterization.•Demonstrating the solution using realistic instances based on large towns. |
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ISSN: | 1366-5545 1878-5794 |
DOI: | 10.1016/j.tre.2023.103216 |