Research on Vehicle Routing Problem in Urban Distribution Using Unmanned Aerial Vehicles

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Tao Li ◽  
Wen-Yin Yang ◽  
Meng-Qing Shen ◽  
Hang Liu
Drones ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 66 ◽  
Author(s):  
Ines Khoufi ◽  
Anis Laouiti ◽  
Cedric Adjih

The use of Unmanned Aerial Vehicles (UAVs) is rapidly growing in popularity. Initially introduced for military purposes, over the past few years, UAVs and related technologies have successfully transitioned to a whole new range of civilian applications such as delivery, logistics, surveillance, entertainment, and so forth. They have opened new possibilities such as allowing operation in otherwise difficult or hazardous areas, for instance. For all applications, one foremost concern is the selection of the paths and trajectories of UAVs, and at the same time, UAVs control comes with many challenges, as they have limited energy, limited load capacity and are vulnerable to difficult weather conditions. Generally, efficiently operating a drone can be mathematically formalized as a path optimization problem under some constraints. This shares some commonalities with similar problems that have been extensively studied in the context of urban vehicles and it is only natural that the recent literature has extended the latter to fit aerial vehicle constraints. The knowledge of such problems, their formulation, the resolution methods proposed—through the variants induced specifically by UAVs features—are of interest for practitioners for any UAV application. Hence, in this study, we propose a review of existing literature devoted to such UAV path optimization problems, focusing specifically on the sub-class of problems that consider the mobility on a macroscopic scale. These are related to the two existing general classic ones—the Traveling Salesman Problem and the Vehicle Routing Problem. We analyze the recent literature that adapted the problems to the UAV context, provide an extensive classification and taxonomy of their problems and their formulation and also give a synthetic overview of the resolution techniques, performance metrics and obtained numerical results.


2019 ◽  
Vol 6 (4) ◽  
pp. 1-11 ◽  
Author(s):  
Mehmet Soysal ◽  
Mustafa Çimen ◽  
Mine Ömürgönülşen ◽  
Sedat Belbağ

This article concerns a green Time Dependent Capacitated Vehicle Routing Problem (TDCVRP) which is confronted in urban distribution planning. The problem is formulated as a Markovian Decision Process and a dynamic programming (DP) approach has been used for solving the problem. The article presents a performance comparison of two recent heuristics for the green TDCVRP that explicitly accounts for time dependent vehicle speeds and fuel consumption (emissions). These heuristics are the classical Restricted Dynamic Programming (RDP) algorithm, and the Simulation Based RDP that consists of weighted random sampling, RDP heuristic and simulation. The numerical experiments show that the Simulation Based Restricted Dynamic Programming heuristic can provide promising results within relatively short computational times compared to the classical Restricted Dynamic Programming for the green TDCVRP.


Sign in / Sign up

Export Citation Format

Share Document