Scholarlink

Natural disasters significantly impact communities, requiring efficient and timely distribution of humanitarian aid. This study proposes an optimization model for delivering aid kits using Unmanned Aerial Vehicles (UAVs) in disaster-affected areas of Oaxaca, Mexico. The methodology involves selecting strategic distribution centers (CEDIS) using the p-median model and optimizing drone delivery routes through the variable neighborhood search (VNS) algorithm. The demand estimation was based on historical disaster data and population statistics, ensuring a realistic approach to resource allocation. Several UAV models were evaluated based on payload capacity, flight time, range, and cost, leading to the selection of the Autel Robotics EVO 2 Pro for its efficiency and affordability. The proposed model minimizes the total travel distance while ensuring maximum coverage within operational constraints. The results demonstrate that combining the p-median model and VNS provides an effective and scalable solution for last-mile humanitarian logistics in emergency scenarios. This research contributes to disaster response planning by leveraging optimization techniques and UAV technology to improve aid distribution efficiency.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Covers the Route to Humanitarian Support Centers with Unmanned Aerial Systems (UAVs)

  • 章节

  • 发表日期：

    2026年

查看全文
  • Irma-Delia Rojas-Cuevas,
  • Diana Sánchez-Partida,
  • Santiago-Omar Caballero-Morales,
  • Juan Díaz-Téllez,
  • José-Rafael Mendoza-Vázquez

摘要

Natural disasters significantly impact communities, requiring efficient and timely distribution of humanitarian aid. This study proposes an optimization model for delivering aid kits using Unmanned Aerial Vehicles (UAVs) in disaster-affected areas of Oaxaca, Mexico. The methodology involves selecting strategic distribution centers (CEDIS) using the p-median model and optimizing drone delivery routes through the variable neighborhood search (VNS) algorithm. The demand estimation was based on historical disaster data and population statistics, ensuring a realistic approach to resource allocation. Several UAV models were evaluated based on payload capacity, flight time, range, and cost, leading to the selection of the Autel Robotics EVO 2 Pro for its efficiency and affordability. The proposed model minimizes the total travel distance while ensuring maximum coverage within operational constraints. The results demonstrate that combining the p-median model and VNS provides an effective and scalable solution for last-mile humanitarian logistics in emergency scenarios. This research contributes to disaster response planning by leveraging optimization techniques and UAV technology to improve aid distribution efficiency.