Szczegóły publikacji
Opis bibliograficzny
A dynamic forecast demand scenario analysis to design an automated parcel lockers network in Pamplona (Spain) using a simulation-optimization model / Irene Izco, Adrian Serrano-Hernandez, Javier Faulin, Bartosz SAWIK // W: WSC 2023 [Dokument elektroniczny] : Winter Simulation Conference : 10-13 December 2023, San Antonio, USA / eds. C. G. Corlu, [et al.]. — Wersja do Windows. — Dane tekstowe. — [Piscataway : IEEE], cop. 2023. — (Proceedings of the Winter Simulation Conference ; ISSN 1558-4305). — Dod. ISBN: 979-8-3503-6967-0. — e-ISBN: 979-8-3503-6966-3. — S. 1759–1770. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 1769–1770, Abstr. — Publikacja dostępna online od: 2024-01-31
Autorzy (4)
- Izco Irene
- Serrano-Hernandez Adrian
- Faulin Javier
- AGHSawik Bartosz
Dane bibliometryczne
| ID BaDAP | 151885 |
|---|---|
| Data dodania do BaDAP | 2024-03-02 |
| Tekst źródłowy | URL |
| DOI | 10.1109/WSC60868.2023.10408738 |
| Rok publikacji | 2023 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Institute of Electrical and Electronics Engineers (IEEE) |
| Konferencja | Winter Simulation Conference 2023 |
| Czasopismo/seria | Proceedings of the Winter Simulation Conference |
Abstract
The disruptions experienced by the last mile delivery processes during the SARS-CoV-2 pandemic have inevitably raised the dilemma of alternative last mile approaches in Urban Logistics (UL). Self-Collection Delivery Systems (SCDS) suppose an improvement for both courier companies and customers, providing flexibility of time-windows and reducing overall mileage, delivery time and, gas emissions. Drawing a distinction from previous works involving hybrid modeling for automated parcel lockers (APL) network design, this study integrates a System Dynamics Simulation Model (SDSM) to forecast e-commerce demand in Pamplona (Spain), and considers the scalability of the model for other cities. A bi-criteria Facility Location Problem (FLP) is proposed and solved with an ε-constraint method, where ε is defined as the level of coverage of the total demand, and four different cases of demand coverage are run. The simulation and demand forecast was carried out using Anylogic software, being CPLEX the optimization solver.
