A Drone Delivery Problem Arising in the Meal Delivery based on VNS Algorithm

The use of drones for delivering various logistics products, including urban express services and food takeout, has emerged as a promising trend. This study explores the optimal strategy for organizing item deliveries in meal delivery logistics and assesses the effectiveness of a comprehensive drone distribution plan throughout the process. In the first stage, the locations of randomly selected distribution facilities are determined. In the second stage, a Variable Neighborhood Search (VNS) algorithm is employed to optimize these locations. The comparison of the VNS with a standard algorithm and a solver highlights the advantages of the VNS method in terms of efficiency and accuracy. This evaluation seeks to provide a more effective calculation approach for real-world logistics challenges, ultimately enhancing the effectiveness of drone delivery systems in practical applications. By demonstrating improved performance metrics, such as reduced delivery times and optimized resource allocation, this study aims to facilitate the broader adoption of drone technology in the logistics industry, paving the way for more innovative solutions.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/icocta64736.2024.00033
Citations
1
Primary Topic
Advanced Technologies in Various Fields
Type
article
Field-Weighted Citation Impact
0.35

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article

A Drone Delivery Problem Arising in the Meal Delivery based on VNS Algorithm

Pan Liu, Benhe Gao, Jie Deng, Yandong He
1 citations
Advanced Technologies in Various Fields
0.35
article

A Drone Delivery Problem Arising in the Meal Delivery based on VNS Algorithm

Pan Liu, Benhe Gao, Jie Deng, Yandong He
article en
1 citations

Abstract

The use of drones for delivering various logistics products, including urban express services and food takeout, has emerged as a promising trend. This study explores the optimal strategy for organizing item deliveries in meal delivery logistics and assesses the effectiveness of a comprehensive drone distribution plan throughout the process. In the first stage, the locations of randomly selected distribution facilities are determined. In the second stage, a Variable Neighborhood Search (VNS) algorithm is employed to optimize these locations. The comparison of the VNS with a standard algorithm and a solver highlights the advantages of the VNS method in terms of efficiency and accuracy. This evaluation seeks to provide a more effective calculation approach for real-world logistics challenges, ultimately enhancing the effectiveness of drone delivery systems in practical applications. By demonstrating improved performance metrics, such as reduced delivery times and optimized resource allocation, this study aims to facilitate the broader adoption of drone technology in the logistics industry, paving the way for more innovative solutions.

Shenzhen Research Institute of Big Data (CN), Tsinghua–Berkeley Shenzhen Institute (CN), Henan Agricultural University (CN), Tsinghua University (CN)
Henan University, Henan Agricultural University, Shenzhen Research Institute of Big Data
Zero hunger
Openalex Percentile: Top 29%
Advanced Technologies in Various Fields
0.35
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