Modeling optimal drone fleet size considering stochastic demand
The last mile delivery is particularly challenging for stochastic deliveries with narrow time windows. This topic is timely due to the rise of e-commerce and courier type services and the impacts of fleet size and vehicle type on delivery costs. A novel contribution of this research is to provide an...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Series: | EURO Journal on Transportation and Logistics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2192437624000025 |
| _version_ | 1797238039386259456 |
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| author | Yuval Hadas Miguel A. Figliozzi |
| author_facet | Yuval Hadas Miguel A. Figliozzi |
| author_sort | Yuval Hadas |
| collection | DOAJ |
| description | The last mile delivery is particularly challenging for stochastic deliveries with narrow time windows. This topic is timely due to the rise of e-commerce and courier type services and the impacts of fleet size and vehicle type on delivery costs. A novel contribution of this research is to provide an optimization approach, extending the newsvendor model, to provide an optimal drone fleet sizing solution with stochastic demand in terms of number of deliveries and deliveries weight or payload from one central depot. The solutions obtained are robust, as shown in a comprehensive sensitivity analysis. |
| first_indexed | 2024-04-24T17:29:18Z |
| format | Article |
| id | doaj.art-5b721a32553147869c8fdc156b3bdb27 |
| institution | Directory Open Access Journal |
| issn | 2192-4384 |
| language | English |
| last_indexed | 2024-04-24T17:29:18Z |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EURO Journal on Transportation and Logistics |
| spelling | doaj.art-5b721a32553147869c8fdc156b3bdb272024-03-28T06:37:44ZengElsevierEURO Journal on Transportation and Logistics2192-43842024-01-0113100127Modeling optimal drone fleet size considering stochastic demandYuval Hadas0Miguel A. Figliozzi1Department of Management, Bar-Ilan University, Ramat Gan, 5290002, IsraelTransportation Technology and People (TTP) Lab, Department of Civil and Environmental Engineering, Portland State University, Portland, OR, 97201, USA; Corresponding author.The last mile delivery is particularly challenging for stochastic deliveries with narrow time windows. This topic is timely due to the rise of e-commerce and courier type services and the impacts of fleet size and vehicle type on delivery costs. A novel contribution of this research is to provide an optimization approach, extending the newsvendor model, to provide an optimal drone fleet sizing solution with stochastic demand in terms of number of deliveries and deliveries weight or payload from one central depot. The solutions obtained are robust, as shown in a comprehensive sensitivity analysis.http://www.sciencedirect.com/science/article/pii/S2192437624000025DroneFleet sizingStochastic demandOptimization |
| spellingShingle | Yuval Hadas Miguel A. Figliozzi Modeling optimal drone fleet size considering stochastic demand EURO Journal on Transportation and Logistics Drone Fleet sizing Stochastic demand Optimization |
| title | Modeling optimal drone fleet size considering stochastic demand |
| title_full | Modeling optimal drone fleet size considering stochastic demand |
| title_fullStr | Modeling optimal drone fleet size considering stochastic demand |
| title_full_unstemmed | Modeling optimal drone fleet size considering stochastic demand |
| title_short | Modeling optimal drone fleet size considering stochastic demand |
| title_sort | modeling optimal drone fleet size considering stochastic demand |
| topic | Drone Fleet sizing Stochastic demand Optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2192437624000025 |
| work_keys_str_mv | AT yuvalhadas modelingoptimaldronefleetsizeconsideringstochasticdemand AT miguelafigliozzi modelingoptimaldronefleetsizeconsideringstochasticdemand |