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Unmanned Aerial Vehicle Inspection Routing and Scheduling for Engineering Management

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Technological advancements in unmanned aerial vehicles(UAVs)have revolutionized various industries,enabling the widespread adoption of UAV-based solutions.In engineering management,UAV-based inspection has emerged as a highly efficient method for identifying hidden risks in high-risk construction environments,surpassing traditional inspection techniques.Building on this foundation,this paper delves into the optimization of UAV inspection routing and scheduling,addressing the complexity intro-duced by factors such as no-fly zones,monitoring-interval time windows,and multiple monitoring rounds.To tackle this challenging problem,we propose a mixed-integer linear programming(MILP)model that optimizes inspection task assignments,monitoring sequence schedules,and charging deci-sions.The comprehensive consideration of these factors differentiates our problem from conventional vehicle routing problem(VRP),leading to a mathematically intractable model for commercial solvers in the case of large-scale instances.To overcome this limitation,we design a tailored variable neighbor-hood search(VNS)metaheuristic,customizing the algorithm to efficiently solve our model.Extensive numerical experiments are conducted to validate the efficacy of our proposed algorithm,demonstrating its scalability for both large-scale and real-scale instances.Sensitivity experiments and a case study based on an actual engineering project are also conducted,providing valuable insights for engineering man-agers to enhance inspection work efficiency.

Engineering managementUnmanned aerial vehicleInspection routing and schedulingoptimizationMixed-integer linear programming modelVariable neighborhood search metaheuristic

Lu Zhen、Zhiyuan Yang、Gilbert Laporte、Wen Yi、Tianyi Fan

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School of Management,Shanghai University,Shanghai 200444,China

Department of Decision Sciences,HEC Montréal,Montréal,QC H3T 2A7,Canada

School of Management,University of Bath,Bath BA2 7AY,UK

Department of Building and Real Estate,The Hong Kong Polytechnic University,Hong Kong 999077,China

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National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of China

72201229720251037239436072394362723611370017207117371831008

2024

10.1016/j.eng.2023.10.014

工程(英文)

工程(英文)

CSTPCDEI
ISSN：2095-8099
年,卷(期)：2024.36(5)