Application of Drone in Solving Last Mile Parcel Delivery
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Jiashi Liu
,
Zhongliang Guan
Abstract
The article is about solving the last mile delivery problem in rural town or village. We want to test the drone’s potential in parcel delivery. The objectives are 1) to introduce the cluster and truck-drone in tandem delivery method, 2) to compare the new method with the traditional TSP method in aspect of truck running distance, energy using and time occupation. The parcel delivery demand is sparse, so it is not dense enough for a truck to carry on delivery. We try to identify the best route for the drone to deliver the goods. We use k-mean method to carry on clustering, then we use enumeration method to fulfill the centroids delivery, which comes from the depot. We design a model and calculate the energy, time and distance saving between drone using method (DTSP) and traditional TSP method. The drone attended delivery saves truck delivery distance, energy consumption and time. The truck running distance of DTSP method saves 91.87%, the truck running distance is shortened from 189.69 km to 15.4252 km. The DTSP method saves 90.45% of energy. The DTSP method brings a 29.75% cutoff in time aspect when there are two drone in running. The research introduces the cluster and TSP combination method, which is a good way to carry on last mile delivery. The result shows a bright future for drone to attend parcel delivery. The e-commerce corporation can apply this method in practice.
References
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Articles in the same Issue
- A KELM-Based Ensemble Learning Approach for Exchange Rate Forecasting
- Application of Drone in Solving Last Mile Parcel Delivery
- The Difference of Capital Input and Productivity in Service Industries: Based on Four Stages Bootstrap-DEA Model
- Parameter Estimation of a Mixed Production Function Model Based on Improved Firefly Algorithm and Model Application
- Analysis of a Discrete-Time Geo/G/1 Queue in a Multi-Phase Service Environment with Disasters
- A New K-Shell Decomposition Method for Identifying Influential Spreaders of Epidemics on Community Networks
- Non-equidistance DGM(1,1) Model Based on the Concave Sequence and Its Application to Predict the China’s Per Capita Natural Gas Consumption
