Applications of unmanned aerial vehicles in logistics
Abstract
Looking to integrate more efficient modes of transport, one of the areas of research and innovation in logistics is the use of unmanned aerial vehicles (drones) which are a technology present within the industry 4.0.
In this article, we review some of the applications of drones in the supply chain which have been extended to different sectors from studies that combine the use of drones and trucks for the efficient delivery of products to aspects related to monitoring and analysis. of sectors such as agro-industry.
The use of drones for the delivery of the last mile in humanitarian logistics is another area of application of these technologies that are being addressed at present. The application of drones is undoubtedly one of the main innovations present that will revolutionize the future of logistics throughout the supply chain. In addition, through of unmanned aerial vehicles it is possible to quickly deliver products to customers, eliminating waiting times and operating costs compared to the traditional use of modes of transport, mainly those that are made by land.
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References
Rodríguez, A y Ruiz, R. (2009). Visualización avanzada de información logística SCM en GIS. 3rd. International Conference on Industrial Engineering and Industrial Management.
Giones, F y Brem, A. (2017). From toys to tools: The co-evolution of technological and entrepreneurial developments in the drone industry. Business Horizons. 1-10.
Haidari, L,A., Brown, S.T., Ferguson, M., Bancroft, E., Spiker, M., Wilcox, A., Ambikapathi., R, Sampath, V., Connor, D,L y Lee, B.Y. (2016). The economic and operational value of using drones to transport vaccines. Vaccine. 4062-4067.
Boysen, N., Briskorn, D., Fedtke, S y Schwerdfeger, S. (2018). Drone delivery from trucks: Drone scheduling for given truck routes.
Gunnar Carlsson, J. y Song, S. (2017). Coordinated Logistics with a Truck and a Drone. Management Science. 1 – 18.
Barmpounakis, E, N., Vlahogianni E,I y Golias, J.C. (2016). Unmanned Aerial Aircraft Systems for transportation engineering: Current practice and future challenges. International Journal of Transportation Science and Technology. 111-122.
Hassanalian, M y Abdelkefi A. (2017). Classification, applications, and design challenges of drones: A review. Progress in Aerospace Sciences. 99-131.
González-Torre, A y Gisbert-Soler, V. (2017). Use of drones in urban distribution. 3C Empresa. 108 – 115.
Murray, C.C. y Chu, A.G. (2015). The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery. Transportation Research Part C. 86-109.
Es-Yurek, Emine y Cenk-Ozmutlu, H. (2018). A descomposition-based iterative optimization algorithm for traveling salesman problem with drone. Transportation Research Part C. 249-262.
Minh-Ha, Q., Deville, Y., Dung-Pham, Q y Hoang-Ha, M. (2018). On the min-cost Traveling Salesman Problem with Drone. Transportation Research Part C. 597-621.
Ham, A.M. (2018). Integrated scheduling of m-truck, m-drone, and m-depot constrained by time-window, drop-pickup, and m-visit using constraint programming. Transportation Research Part C. 1-14.
Mbiadou-Saleu, R.G., Deroussi, L., Feillet, D., Grangeon, N y Quilliot, A. (2018). An iterative two-step heuristic for the parallel drone scheduling traveling salesman problem. Networks. 1-16.
Kim, S y Moon, I. (2019). Traveling Salesman Problem With a Drone Station. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 42-52.
Chowdhury, S., Emelogu, A., Marufuzzaman, M., Nurre S.G y Bian, L. (2017). Drones for disaster response and relief operations: A continuous approximation model. International Journal of Production Economics. 167-184.
Rabta, B., Wankmuller, C. y Reiner, G. (2018). A drone fleet model for last-mile distribution in disaster relief operations. International Journal of Disaster Risk Reduction. 107-112.
Granillo-Macías, R., Olivares-Benítez, E., Martínez-Flores, J y Caballero-Morales, S. (2018). Analysis of logistics cost in contract agriculture: the case of barley supply chain in Hidalgo, Mexico. Custos e agronegocio on line. 164-183.
Chhetri, P., Kam, B., Hung Lau, K., Corbitt, B y Cheong, F. (2017). Improving service responsiveness and delivery efficiency of retail networks: A case study of Melbourne. International Journal of Retail & Distribution Management. 45, 271-291
Trubint, N., ljubomir, O. and Nebojsa, B. (2006), “Determining an optimal retail location by using GIS”, Yogoslav Journal of Operations Research, 16, 253-264.
Sharma, R., Kamble, S.S. y Gunasekaran, A. (2018). Big GIS analytics framework for agricultura supply chains: A literature review identifying the current trends and future perspectives. Computers and Electronics in Agriculture. 103-120.
Kulbacki, M., Segen, J., Kniec, W., Klempous, R., Kluwak, K., Nikode,. J., Kulbacka, J y Serester, A. (2018). Survey of drones for agriculture automation from planting to harvest. International Conference on Intelligent Engineering Systems. IEEE. 353-358.
FAO. (2018). E- agriculture in action: Drones for agriculture. Gerard Sylvester, Editor. Recuperado el (30/03/2019) de http://www.fao.org/3/i8494en/i8494en.pdf .
