Optimal hub selection for rapid medical deliveries using unmanned aerial vehicles

Abstract Unmanned Aerial Vehicles (UAVs) are being increasingly deployed in humanitarian response operations. Beyond regulations, vehicle range and integration with the humanitarian supply chain inhibit their deployment. To address these issues, we present a novel bi-stage operational planning approach that consists of a trajectory optimisation algorithm (that considers multiple flight stages), and a hub selection-routing algorithm that incorporates a new battery management heuristic. We apply the algorithm to a hypothetical response mission in Taiwan after the Chi-Chi earthquake of 1999 considering mission duration and distribution fairness. Our analysis indicates that UAV fleets can be used to provide rapid relief to populations of 20,000 individuals in under 24 h. Additionally, the proposed methodology achieves significant reductions in mission duration and battery stock requirements with respect to conservative energy estimations and other heuristics.

[1]  David L. Woodruff,et al.  Pyomo: modeling and solving mathematical programs in Python , 2011, Math. Program. Comput..

[2]  Jonathan P. How,et al.  Automated Battery Swap and Recharge to Enable Persistent UAV Missions , 2011 .

[3]  G. Laporte,et al.  An exact algorithm for solving a capacitated location-routing problem , 1986 .

[4]  Chinyao Low,et al.  Heuristic solutions to multi-depot location-routing problems , 2002, Comput. Oper. Res..

[5]  Bruce L. Golden,et al.  The vehicle routing problem with drones: several worst-case results , 2017, Optim. Lett..

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

[7]  L. V. Wassenhove,et al.  On the appropriate objective function for post‐disaster humanitarian logistics models , 2013 .

[8]  Robert Brian Stoney.  Design, Fabrication and Test of a Vertical Attitude Takeoff and Landing Unmanned Air Vehicle , 1993 .

[9]  Alan T. Murray,et al.  A range-restricted recharging station coverage model for drone delivery service planning , 2018 .

[10]  J. Betts.  Survey of Numerical Methods for Trajectory Optimization , 1998 .

[11]  Miguel A. Figliozzi,et al.  Maximum coverage capacitated facility location problem with range constrained drones , 2019, Transportation Research Part C: Emerging Technologies.

[12]  Raffaello D'Andrea,et al.  Guest Editorial Can Drones Deliver? , 2014, IEEE Trans Autom. Sci. Eng..

[13]  H. C. Ozmutlu,et al.  A decomposition-based iterative optimization algorithm for traveling salesman problem with drone , 2018, Transportation Research Part C: Emerging Technologies.

[14]  Kaan Ozbay,et al.  A Secure and Efficient Inventory Management System for Disasters , 2013 .

[15]  David Pisinger,et al.  Large Neighborhood Search , 2018, Handbook of Metaheuristics.

[16]  Bruce L. Golden,et al.  The multi-depot split delivery vehicle routing problem: An integer programming-based heuristic, new test problems, and computational results , 2011, Comput. Ind. Eng..

[17]  John F. Keane,et al.  A Brief History of Early Unmanned Aircraft , 2013 .

[18]  Michael S. Selig,et al.  Propeller Performance Data at Low Reynolds Numbers , 2011 .

[19]  W. Gracey.  Measurement of aircraft speed and altitude , 1981 .

[20]  Mark S. Daskin,et al.  A warehouse location-routing problem , 1985 .

[21]  Martin Stynes,et al.  Numerical Treatment of Partial Differential Equations , 2007 .

[22]  Gokhan Izbirak,et al.  Post-earthquake response by small UAV helicopters , 2016, Natural Hazards.

[23]  L. Fanucci,et al.  State-of-charge estimation enhancing of lithium batteries through a temperature-dependent cell model , 2011, 2011 International Conference on Applied Electronics.

[24]  富野 康日己,et al.  Annual review 腎臓 , 1987 .

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

[26]  Hsian J. Wang,et al.  Disaster epidemiology and medical response in the Chi-Chi earthquake in Taiwan. , 2001, Annals of emergency medicine.

[27]  David Pisinger,et al.  An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones , 2019, Transportation Research Part C: Emerging Technologies.

[28]  Yao-Nan Lien,et al.  Challenges of emergency communication network for disaster response , 2012, 2012 IEEE International Conference on Communication Systems (ICCS).

[29]  James R. Morrison,et al.  Automatic Battery Replacement System for UAVs: Analysis and Design , 2011, Journal of Intelligent & Robotic Systems.

[30]  Jiuh-Biing Sheu,et al.  An emergency logistics distribution approach for quick response to urgent relief demand in disasters , 2007 .

[31]  Juan A. Díaz,et al.  A compact model and tight bounds for a combined location-routing problem , 2005, Comput. Oper. Res..

[32]  Kaan Ozbay,et al.  An RFID-based inventory management framework for emergency relief operations , 2015 .

[33]  Linet Özdamar,et al.  Planning helicopter logistics in disaster relief , 2011, OR Spectr..

[34]  Gülay Barbarosoglu,et al.  An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations , 2002, Eur. J. Oper. Res..

[35]  Cem Iyigun,et al.  Locating emergency vehicles with an approximate queuing model and a meta-heuristic solution approach , 2018 .

[36]  Corey Schumacher,et al.  UAV Scheduling via the Vehicle Routing Problem with Time Windows , 2007 .

[37]  M. Wasner,et al.  An integrated multi-depot hub-location vehicle routing model for network planning of parcel service , 2004 .

[38]  David L. Woodruff,et al.  Pyomo — Optimization Modeling in Python , 2012, Springer Optimization and Its Applications.

[39]  Irving M Gottlieb,et al.  Practical Electric Motor Handbook , 1997 .

[40]  David Linden,et al.  Handbook of batteries and fuel cells , 1984 .

[41]  Rohan Bennett,et al.  Review of the Current State of UAV Regulations , 2017, Remote. Sens..

[42]  Lorenz T. Biegler,et al.  Dynamic Optimization Strategies for Three-Dimensional Conflict Resolution of Multiple Aircraft , 2004 .

[43]  Henry C. W. Lau,et al.  A hybrid genetic algorithm for the multi-depot vehicle routing problem , 2008, Eng. Appl. Artif. Intell..

[44]  Yeong-Dae Kim,et al.  A systematic procedure for setting parameters in simulated annealing algorithms , 1998, Comput. Oper. Res..

[45]  Anjan Chakrabarty,et al.  Flight Path Planning for UAV Atmospheric Energy Harvesting Using Heuristic Search , 2010 .

[46]  Giovanni Storchi,et al.  Multiperiod integrated routing and scheduling of World Food Programme cargo planes in Angola , 2007, Comput. Oper. Res..

[47]  Brian Raymond Geiger,et al.  Unmanned Aerial Vehicle Trajectory Planning with Direct Methods , 2009 .

[48]  Erik Johannes Forsmo,et al.  Optimal Path Planning for Unmanned Aerial Systems , 2012 .

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

[50]  Jiuh-Biing Sheu,et al.  Dynamic Relief-Demand Management for Emergency Logistics Operations Under Large-Scale Disasters , 2010 .

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

[52]  Linet Özdamar,et al.  A dynamic logistics coordination model for evacuation and support in disaster response activities , 2007, Eur. J. Oper. Res..

[53]  Zongzhi Li,et al.  A double standard model for allocating limited emergency medical service vehicle resources ensuring service reliability , 2016 .

[54]  Mahdi Moeini,et al.  A matheuristic for the vehicle routing problem with drones and its variants , 2019, Transportation Research Part C: Emerging Technologies.

[55]  M. Soler,et al.  Conflict pattern analysis under the consideration of optimal trajectories in the European ATM , 2015 .

[56]  Jose B. Cruz,et al.  GENETIC ALGORITHM FOR TASK ALLOCATION IN UAV COOPERATIVE CONTROL , 2003 .

[57]  Luk N. Van Wassenhove,et al.  Using OR to adapt supply chain management best practices to humanitarian logistics , 2012, Int. Trans. Oper. Res..

[58]  Paolo Toth,et al.  The Time Dependent Traveling Salesman Planning Problem in Controlled Airspace , 2016 .

[59]  S. Nash,et al.  Linear and Nonlinear Optimization , 2008 .

[60]  Andy M. Ham,et al.  Integrated scheduling of m-truck, m-drone, and m-depot constrained by time-window, drop-pickup, and m-visit using constraint programming , 2018, Transportation Research Part C: Emerging Technologies.

[61]  Shawn T Brown,et al.  The economic and operational value of using drones to transport vaccines. , 2016, Vaccine.

[62]  Lorenz T. Biegler,et al.  Trajectory Control of Multiple Aircraft: An NMPC Approach , 2007 .

[63]  Keita Higuchi,et al.  Endless Flyer: A Continuous Flying Drone with Automatic Battery Replacement , 2013, 2013 IEEE 10th International Conference on Ubiquitous Intelligence and Computing and 2013 IEEE 10th International Conference on Autonomic and Trusted Computing.

[64]  Timothy W. McLain,et al.  Performance Flight Testing of Small, Electric Powered Unmanned Aerial Vehicles , 2009 .

[65]  Jain-Shing Wu,et al.  Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling , 2014, Expert Syst. Appl..

[66]  Inci Saricicek,et al.  Unmanned Aerial Vehicle hub-location and routing for monitoring geographic borders , 2015 .

[67]  Benita M. Beamon,et al.  Facility location in humanitarian relief , 2008 .

[68]  Ian M. Mitchell,et al.  Multiple aircraft deconflicted path planning with weather avoidance constraints , 2007 .