Analysis and Optimization of DroneGo Disaster Response System
DOI: 10.23977/erej.2020.040101 | Downloads: 13 | Views: 1095
Ziwen Fang 1
1 Institute of international education, North China Electric Power University, Baoding 071000, China
Corresponding AuthorZiwen Fang
Natural disasters can be destructive and cause a wide range of attacks, thus emergent rescue can be crucial. DroneGo disaster response system play an important role in the rescue after disasters. DroneGo fleet is expected to provide both transportation of medical packages and video of damaged and serviceable transportation road networks. We take the hurricane happened in Puerto Rico in 2017 as an example to analyse the DroneGo system. Firstly we develop integer programming model to find the best packing configuration. Then, the selection of locations to position cargo containers can be variant. In order to find the optimal solution, we use level analytical method and develop multiple attribute decision-making model. Finally, the genetic algorithm plays a vital role in optimization of air routes. In addition, we combine the solution to the packing problem and optimal locations to position cargo containers, thus the packing configuration and flight plans are determined. Schedule can be the summary of the previous questions. We make the table for clear explanation.
KEYWORDSDrone, disaster, rescue, optimization
CITE THIS PAPER
Ziwen Fang. Analysis and Optimization of DroneGo Disaster Response System. Environment, Resource and Ecology Journal (2020) 4: 1-15. DOI: http://dx.doi.org/10.23977/erej.2020.040101.
 Ho Young Jeong, Seokcheon Lee, Byung Duk Song Truck-Drone Hybrid Delivery Routing: Payload-Energy dependency and No-Fly Zones International Journal of Production Economics, 10.1016/j.ijpe.2019.01.010 .
 Wikipedia: Genetic Algorithm. 2018.11.26. https://en.wikipedia.org/wiki/Genetic_Algorithm
 Wikipedia: Particle Swarm Optimization. 2018.9.15.
 ZHANG J N, LIU Y N, WANG G UAV route planning based on PSO algorithm [J]. Transducer and Microsystem Tech- nologies, 1000-9787(2017)03-0058-04
 YU H D, WANG C Q, JIA F, LIU Yang, et al. Path Planning for Multiple UAVs Based on Hybrid Particle Swarm Optimization with Differential Evolution [J]. Electronics Optics& Control , 2018, 25(5): 22-25, 45.
 Google:Maps. https:google.cn/maps/place/
 CAO L Q, WU L W, Route Planning for drones base on the genetic algorithm [J].Technology Innovation and Application, 2018, 24(5): 24-0027-04.