A vehicle routing problem arising in unmanned aerial monitoring

Significance 

Recent technological advancement have seen the increase in the use of drones for different applications like military and video shooting owing to their high efficiency, low cost, reliability and real-time operations. Drones are the aerial vehicles that do not require human operators aboard. They have an interconnection of controllers, sensors and communications systems thus can monitor wide areas at ago. Unfortunately, the varying nature of applications of the unmanned aerial vehicles require different accuracy grades. On the other hand, the time required to carry out a particular monitoring operation depends on the height of the unmanned aerial vehicles. Therefore, a drone required to monitor several areas with different accuracy grades within a limited flight time requires routing and height optimization. Thus, researchers have been looking for different alternatives to address the challenge and have identified integer linear programming as a promising solution.

Shanghai University scientists Professor Lu Zhen, Miss Miao Li and Dr. Wencheng Wang in collaboration with Professor Gilbert Laporte at HEC Montreal in Canada developed an unmanned aerial vehicle model for routing and height selection. The authors used linear programming formula and tailored tabu search metaheuristic to obtain large scale instances solutions with fewer computations. Additionally, apart from determining the order followed in visiting the set nodes, the model also determines the height in which the node is visited. They purposed to achieve a minimal time for the tasks monitoring. Their work is currently published in the research journal, Computers and Operational Research.

To achieve their goals, it was necessary for the authors to carry out numerical experiments. For example the authors observed that the developed tabu search metaheuristic model was very efficient due to feasible solutions. For instance, it worked well with bigger instance sizes as compared to the initially used CPLEX linear programming solvers. Furthermore, it considered minimizing the number of unmanned aerial vehicles as well as other key factors during various monitoring operations. Since the all the areas to be monitored are assigned a particular soft time window, the effectiveness of the whole systems can be verified from the time at which the drone starts to monitor the particular required area.

The study successfully proposed a model for routing and height selection problem in unmanned aerial vehicles. It forms the basis for the new unmanned aerial vehicles routing problem studies despite the trade-offs between the study and the actual reality such as the varying velocities of the unmanned vehicles depending on the altitudes. Consequently, the study also takes into account the minimization of the number of unmanned aerial vehicles and other relevant factors during different scheduled monitoring operations.

Therefore, considering the increasing use of drones in different applications, Professor Lu Zhen and his colleagues are optimistic that the study will advance the design and development of more efficient drones fit for various operations. For example, future models will be extended to dynamic scenarios that also takes into consideration the varying velocities. Their study will further allow efficient energy consumption management for the unmanned aerial vehicles.

A vehicle routing problem arising in unmanned aerial monitoring - Advances in Engineering A vehicle routing problem arising in unmanned aerial monitoring - Advances in Engineering A vehicle routing problem arising in unmanned aerial monitoring - Advances in Engineering A vehicle routing problem arising in unmanned aerial monitoring - Advances in Engineering A vehicle routing problem arising in unmanned aerial monitoring - Advances in Engineering A vehicle routing problem arising in unmanned aerial monitoring - Advances in Engineering A vehicle routing problem arising in unmanned aerial monitoring - Advances in Engineering

About the author

Lu Zhen obtained his B.E. and Ph.D. degrees from Shanghai Jiao Tong University in 2003 and 2008, respectively. He is a Professor and a Vice Dean in the School of Management, Shanghai University, Shanghai, China. He His research focuses on logistics and supply chain optimization. He has published 60 scientific articles on renowned journals such as Transportation Science, Transportation Research Part B, Naval Research Logistics, and IISE Transactions.

He serves as an Associate Editor of Journal of the Operational Research Society, IMA Journal of Management Mathematics, Asia-Pacific Journal of Operational Research, Journal of Industrial and Production Engineering, etc.

About the author

Miao Li is a postgraduate in the School of Management, Shanghai University, Shanghai, China. Her research focuses on unmanned aerial routing (UAV) and scheduling. She has published six scientific articles on journals such as Computers & Operations Research, Computers & Industrial Engineering, Transportation Research Part D and International Journal of Shipping and Transport Logistics.

About the author

Gilbert Laporte obtained his Ph.D. in Operations Research at the London School of Economics in 1975. He is a professor of Operations Research at HEC Montréal, Canada Research Chair in Distribution Management, adjunct professor at Molde University College, honorary visiting professor at the University of Liverpool, and distinguished professor at the Eindhoven University of Technology. He is also a member of the Inter-university Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT) and founding member of the Group for Research in Decision Analysis (GERAD).

He has been Editor of renowned journals such as Transportation Science, Computers & Operations Research and INFOR. He has authored or coauthored 19 books, as well as more than 550 scientific articles in combinatorial optimization, mostly in the areas of vehicle routing, location and timetabling.

Bio sketch,  Google Scholar profile

About the author

Wencheng Wang is a Ph.D. in the School of Management, Shanghai University, Shanghai, China. Her research focuses on scheduling and optimization of container terminal. She has published five scientific articles on journals such as Computers & Operations Research, International Journal of Shipping and Transport Logistics and Transportation Research Part C.

Reference

Zhen, L., Li, M., Laporte, G., & Wang, W. (2019). A vehicle routing problem arising in unmanned aerial monitoring. Computers & Operations Research, 105, 1-11.

Go To Computers & Operations Research

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