택배 위치 클러스터링과 RGSO 병렬 트럭-드론 스케줄링

The objective of this paper is to propose two steps truck and drone delivery model based on Parallel Drone Scheduling TSP (PDSTSP) to minimize the completion time that is the time at which the truck and drones return to the depot. In step 1, all delivery positions are clustered based on the relative distance rate of each delivery position and distance between central position data of each cluster. The average of all delivery positions of clusters can be the centroid for tentative drone station to overcome the flight range limitation of drone. The truck and drone station depart from depot to the centroid of each cluster. The truck and drone station are separated each other and the drone station is established in the centroid of each cluster. In step 2, Routing Group Search Optimization (RGSO) is used to find the best schedule and routing of the truck and drone from each centroid to better balance vehicle and drone delivery which can complement drone and truck delivery services. After finishing the deliveries, the truck and drone station are combined and return to depot. Our simulation results show that our methodology is very effective based on the several experiments and analysis.