Node and Edge Drone Surveillance Problem With Consideration of Required Observation Quality and Battery Replacement

Our study introduces a drone routing problem in which drones fly to capture photos for surveillance purposes after a disaster. The drones perform observations on nodes and edges representing populated areas and road segments of a network from multiple altitudes. Each target node and edge requires observation at least once with a certain required quality. When the drones fly at a relatively high altitude, they can simultaneously capture low-quality photos and a large number of observed target nodes and edges. However, high-quality photos and narrow observation areas can be captured from a relatively low altitude. Each drone has a limited battery capacity and thus must return to the depot for battery replacement. This study routes the drones to satisfy the required photo quality of all target nodes and edges while minimizing the makespan of the surveillance by all drones. Our study is the first to examine a multiple-drone routing problem while considering flight altitude-dependent observation quality, battery replacement, node and edge combination, and minimizing the makespan. Our problem is formulated as a mixed integer linear programming (MILP) model. Firefly and adaptive–reactive tabu search algorithms are proposed. The latter outperforms the former and obtains better solutions than those in the MILP model for small-sized instances within a given short computation time.

[1]  Rakesh Nagi,et al.  Simultaneous sensor selection and routing of unmanned aerial vehicles for complex mission plans , 2012, Comput. Oper. Res..

[2]  Jose B. Cruz,et al.  Stable Cooperative Surveillance With Information Flow Constraints , 2008, IEEE Transactions on Control Systems Technology.

[3]  M. Sayadi,et al.  A discrete firefly meta-heuristic with local search for makespan minimization in permutation flow shop scheduling problems , 2010 .

[4]  Zhong Liu,et al.  Cooperative Routing Problem for Ground Vehicle and Unmanned Aerial Vehicle: The Application on Intelligence, Surveillance, and Reconnaissance Missions , 2019, IEEE Access.

[5]  N. Labadi,et al.  Tour splitting algorithms for vehicle routing problems , 2009 .

[6]  Chunfeng Wang,et al.  An Improved Firefly Algorithm With Specific Probability and Its Engineering Application , 2019, IEEE Access.

[7]  Lixin Ding,et al.  A Multi-population Discrete Firefly Algorithm to Solve TSP , 2014, BIC-TA.

[8]  Zhibin Jiang,et al.  A memetic algorithm with iterated local search for the capacitated arc routing problem , 2013 .

[9]  Purushothaman Damodaran,et al.  Lower Bounds For Hierarchical Chinese Postman Problem , 2008 .

[10]  Xin-She Yang,et al.  Efficiency Analysis of Swarm Intelligence and Randomization Techniques , 2012, 1303.6342.

[11]  Chungmok Lee,et al.  Benders-and-Price approach for electric vehicle charging station location problem under probabilistic travel range , 2017 .

[12]  Agathoniki Trigoni,et al.  Probabilistic target detection by camera-equipped UAVs , 2010, 2010 IEEE International Conference on Robotics and Automation.

[13]  Agathoniki Trigoni,et al.  Supporting Search and Rescue Operations with UAVs , 2010, 2010 International Conference on Emerging Security Technologies.

[14]  Christos D. Tarantilis,et al.  An Adaptive Memory Programming Framework for the Robust Capacitated Vehicle Routing Problem , 2016, Transp. Sci..

[15]  Hanil Jeong,et al.  A Solution Procedure for Emergency Logistics Problem in Disaster Scene , 2018 .

[16]  Gábor Nagy,et al.  A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries , 2008, J. Comb. Optim..

[17]  Xin-She Yang,et al.  Firefly Algorithm: Recent Advances and Applications , 2013, ArXiv.

[18]  Chang-Guk Sun,et al.  Geospatial Assessment of the Post-Earthquake Hazard of the 2017 Pohang Earthquake Considering Seismic Site Effects , 2018, ISPRS Int. J. Geo Inf..

[19]  Lin Ma,et al.  Skill Vehicle Routing Problem With Time Windows Considering Dynamic Service Times and Time-Skill-Dependent Costs , 2019, IEEE Access.

[20]  Dimitrios Zorbas,et al.  Optimal drone placement and cost-efficient target coverage , 2016, J. Netw. Comput. Appl..

[21]  Mohammad Marufuzzaman,et al.  Drones for disaster response and relief operations: A continuous approximation model , 2017 .

[22]  Wencheng Wang,et al.  A vehicle routing problem arising in unmanned aerial monitoring , 2019, Comput. Oper. Res..

[23]  Vitor Nazário Coelho,et al.  A multi-objective green UAV routing problem , 2017, Comput. Oper. Res..

[24]  D. Ghose,et al.  Search using multiple UAVs with flight time constraints , 2004, IEEE Transactions on Aerospace and Electronic Systems.

[25]  Michael A. Goodrich,et al.  Supporting wilderness search and rescue using a camera‐equipped mini UAV , 2008, J. Field Robotics.

[26]  Sebastian Magierowski,et al.  Vehicle Routing Problems for Drone Delivery , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[27]  Chase C. Murray,et al.  The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery , 2015 .

[28]  Absalom E. Ezugwu,et al.  An Improved Firefly Algorithm for the Unrelated Parallel Machines Scheduling Problem With Sequence-Dependent Setup Times , 2018, IEEE Access.

[29]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[30]  Ertan Yakici,et al.  Solving location and routing problem for UAVs , 2016, Comput. Ind. Eng..

[31]  Raman Maini,et al.  A hybrid of ant colony and firefly algorithms (HAFA) for solving vehicle routing problems , 2018, J. Comput. Sci..

[32]  Milan Simic,et al.  Investigation in Wireless Power Transmission for UAV Charging , 2015, KES.

[33]  David Camacho,et al.  Analysing temporal performance profiles of UAV operators using time series clustering , 2016, Expert Syst. Appl..

[34]  Xin-She Yang,et al.  A Discrete Firefly Algorithm for the Multi-Objective Hybrid Flowshop Scheduling Problems , 2014, IEEE Transactions on Evolutionary Computation.

[35]  Woon-Seek Lee,et al.  A Stock Pre-positioning Model to Maximize the Total Expected Relief Demand of Disaster Areas , 2014 .

[36]  B. S. Karthik Reddy,et al.  Performance analysis of solar powered Unmanned Aerial Vehicle , 2017 .

[37]  Suyanto,et al.  Discrete Firefly Algorithm for Traveling Salesman Problem: A New Movement Scheme , 2013 .

[38]  Xin-She Yang,et al.  A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy , 2016, Soft Computing.

[39]  Yves Deville,et al.  On the Min-cost Traveling Salesman Problem with Drone , 2015, ArXiv.

[40]  Jay M. Rosenberger,et al.  Unmanned aerial vehicle routing in the presence of threats , 2018, Comput. Ind. Eng..

[41]  Arturo de la Escalera,et al.  Survey of computer vision algorithms and applications for unmanned aerial vehicles , 2018, Expert Syst. Appl..

[42]  Joseph Y. J. Chow.  Dynamic UAV-based traffic monitoring under uncertainty as a stochastic arc-inventory routing policy , 2016, 1609.03201.

[43]  N. Wassan.  Reactive tabu adaptive memory programming search for the vehicle routing problem with backhauls , 2007, J. Oper. Res. Soc..

[44]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .