Scheduling and route planning of unmanned aerial vehicle for multi-parcel postal delivery in Singapore

Electronic commerce, or eCommerce, has been gaining popularity in recent years, and studies have shown that the COVID-19 pandemic has caused the market share of online sales to grow much faster than before. However, the fulfilment of online orders has been met with logistic problems such as manpower...

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Bibliographic Details
Main Author: Voo, Amber E Ning
Other Authors: Sivakumar Appa Iyer,Siva
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/168366
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Institution: Nanyang Technological University
Language: English
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Summary:Electronic commerce, or eCommerce, has been gaining popularity in recent years, and studies have shown that the COVID-19 pandemic has caused the market share of online sales to grow much faster than before. However, the fulfilment of online orders has been met with logistic problems such as manpower and vehicle shortages. As such, many industry giants and researchers are looking into UAVs as an alternative solution to the traditional truck delivery system. There are several limitations to using UAVs in delivery. They are only able to carry a few packages due to limitations in size as well as allowable payload. In contrast, trucks are able to carry numerous packages of various weights. However, where trucks are bounded by roads that are affected by congestion as well as manpower availability, UAVs can contribute to the delivery system. Hence, an alternative delivery system that pairs one drone and one truck was designed in this project to leverage the advantages of these two separate delivery modes. Algorithms were developed to schedule delivery routes that will be able to incorporate the drone into the traditional truck-only delivery route. Results showed that maximising drone usage in the delivery route optimises the time taken to complete the route. The designed system also provided an average time saving of 11% compared to the traditional delivery system. The system was also shown to be feasible by analysing the energy consumption of the drone throughout the route.