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Application of hierarchical facility location problem for optimization of a drone delivery system: a case study of Amazon prime air in the city of San Francisco

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Abstract

In the last decade, aerial delivery system has been considered as a promising response to increasing traffic jams and incremental demand for transportation. In this study, a distance-constrained mobile hierarchical facility location problem is used in order to find the optimal number and locations of launch and recharge stations with the objective of minimizing the total costs of the system. System costs include establishment cost for launching and recharge stations, drone procurement, and drone usage costs. It is supposed that the demand occurs according to Poisson distribution, distributed uniformly along the network edges and is satisfied by the closest open facility. Since the flying duration of a drone is limited to its endurance, it may visit one or more recharge stations to reach to the demand point. This route is calculated by the shortest path algorithm, and the Euclidean distance is considered between nodes and facilities. It is proved that facility location problems are NP-hard on a general graph. Accordingly, heuristic algorithms are proposed as solution method. To illustrate the applicability of the algorithms, a case study is presented and the results are discussed.

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References

  1. Ahmadi T, Karimi H, Davoudpour H, Hosseinijou SA (2015) A robust decision-making approach for p-hub median location problems based on two-stage stochastic programming and mean-variance theory: a real case study. Int J Adv Manuf Technol 77(9–12):1943–1953. https://doi.org/10.1007/s00170-014-6569-x

    Article  Google Scholar 

  2. Basti M, Sevkli M (2015) An artificial bee colony algorithm for the p-median facility location problem. Int J Met 4(1):91. https://doi.org/10.1504/IJMHEUR.2015.071769

    Google Scholar 

  3. Bhattacharya R, Bandyopadhyay S (2010) Solving conflicting bi-objective facility location problem by NSGA II evolutionary algorithm. Adv Manuf Technol Retrieved from 51(1-4):397–414. https://doi.org/10.1007/s00170-010-2622-6

    Article  Google Scholar 

  4. Camacho-Vallejo J-F, Cordero-Franco ÁE, González-Ramírez RG (2014) Solving the bilevel facility location problem under preferences by a Stackelberg-evolutionary algorithm. Math Probl Eng 2014:1–14. https://doi.org/10.1155/2014/430243

    Article  MathSciNet  Google Scholar 

  5. D’Andrea R (2014) Guest editorial can drones deliver? IEEE Trans Autom Sci Eng 11(3):647–648. https://doi.org/10.1109/TASE.2014.2326952

    Article  Google Scholar 

  6. Dorling K, Heinrichs J, Messier GG, Magierowski S (2017a) Vehicle routing problems for drone delivery. IEEE Transactions on Systems, Man, and Cybernetics: Systems 47(1):70–85. https://doi.org/10.1109/tsmc.2016.2582745

    Article  Google Scholar 

  7. Dorling K, Heinrichs J, Messier GG, Magierowski S (2017b) Vehicle routing problems for drone delivery. IEEE Trans Syst Man and Cybernetics: Systems 47(1):70–85. https://doi.org/10.1109/TSMC.2016.2582745

    Article  Google Scholar 

  8. Farahani RZ, Hekmatfar M, Fahimnia B, Kazemzadeh N (2014) Hierarchical facility location problem: models, classifications, techniques, and applications. Comput Ind Eng 68:104–117. https://doi.org/10.1016/j.cie.2013.12.005

    Article  Google Scholar 

  9. Fernandes DRM, Rocha C, Aloise D, Ribeiro GM, Santos EM, Silva A (2014) A simple and effective genetic algorithm for the two-stage capacitated facility location problem. Comput Ind Eng 75:200–208. https://doi.org/10.1016/j.cie.2014.05.023

    Article  Google Scholar 

  10. Ghaderi A, Rahmaniani R (2016) Meta-heuristic solution approaches for robust single allocation p-hub median problem with stochastic demands and travel times. Int J Adv Manuf Technol 82(9–12):1627–1647. https://doi.org/10.1007/s00170-015-7420-8

    Article  Google Scholar 

  11. Golabi M, Shavarani SM, Izbirak G (2017a) An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran earthquake. Nat Hazards 87(3):1–21. https://doi.org/10.1007/s11069-017-2832-4

    Article  Google Scholar 

  12. Golabi M, Shavarani SM, Izbirak G (2017b) An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran earthquake. Nat Hazards 87(3):1–21. https://doi.org/10.1007/s11069-017-2832-4

    Article  Google Scholar 

  13. Gonçalves JF, Resende MGC (2015) A biased random-key genetic algorithm for the unequal area facility layout problem. Eur J Oper Res 246(1):86–107. https://doi.org/10.1016/j.ejor.2015.04.029

    Article  MathSciNet  MATH  Google Scholar 

  14. Goodchild A, Toy J (2017) Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO 2 emissions in the delivery service industry. Transp Res Part D: Transp Environ https://doi.org/10.1016/j.trd.2017.02.017

  15. Gross D (2013) Amazon’s drone delivery: how would it work?—CNN. Retrieved October 26, 2017, from http://edition.cnn.com/2013/12/02/tech/innovation/amazon-drones-questions/

  16. Guo P, Cheng W, Wang Y (2017) Hybrid evolutionary algorithm with extreme machine learning fitness function evaluation for two-stage capacitated facility location problems. Expert Syst Appl 71:57–68. https://doi.org/10.1016/j.eswa.2016.11.025

    Article  Google Scholar 

  17. Haidari LA, Brown ST, Ferguson M, Bancroft E, Spiker M, Wilcox A, Ambikapathi R, Sampath V, Connor DL, Lee BY (2016) The economic and operational value of using drones to transport vaccines. Vaccine 34(34):4062–4067. https://doi.org/10.1016/j.vaccine.2016.06.022

    Article  Google Scholar 

  18. Helber S, Böhme D, Oucherif F, Lagershausen S, Kasper S (2016) A hierarchical facility layout planning approach for large and complex hospitals. Flex Serv Manuf J 28(1–2):5–29. https://doi.org/10.1007/s10696-015-9214-6

    Article  Google Scholar 

  19. Ho S (2015) An iterated tabu search heuristic for the single source capacitated facility location problem. Appl Soft Comput Retrieved from http://www.sciencedirect.com/science/article/pii/S1568494614005560 27:169–178. https://doi.org/10.1016/j.asoc.2014.11.004

    Article  Google Scholar 

  20. Holland, J. H. (1975). Adaptation in Natural and Artificial Systems. (null, Ed.) (Vol. null)

  21. Hong I, Kuby M, Murray A (2017a) A deviation flow refueling location model for continuous space: a commercial drone delivery system for urban areas. Springer, Cham, pp 125–132. https://doi.org/10.1007/978-3-319-22786-3_12

    Google Scholar 

  22. Hong I, Kuby M, Murray A (2017b) A deviation flow refueling location model for continuous space: a commercial drone delivery system for urban areas. Springer, Cham, pp 125–132. https://doi.org/10.1007/978-3-319-22786-3_12

    Google Scholar 

  23. Jansen B (2014) FAA approves first commercial drone over land. Retrieved October 25, 2017, from https://www.usatoday.com/story/money/business/2014/06/10/faa-drones-bp-oil-pipeline-aerovironment-north-shore/10264197/

  24. Karkazis J, Boffey TB (1981) The multi-commodity facilities location problem. J Oper Res Soc 32(9):803. https://doi.org/10.2307/2581396

    Article  MathSciNet  MATH  Google Scholar 

  25. Kazemi A, Zarandi M, Husseini S (2009) A multi-agent system to solve the production–distribution planning problem for a supply chain: a genetic algorithm approach. Manuf Technol Retrieved from 44(1-2):180–193. https://doi.org/10.1007/s00170-008-1826-5

    Article  Google Scholar 

  26. Khanduzi R, Peyghami MR, Maleki HR (2014) Solving continuous single-objective defensive location problem based on hybrid directed tabu search algorithm. Int J Adv Manuf Technol 76(1–4):295–310. https://doi.org/10.1007/s00170-014-6180-1

    Google Scholar 

  27. Kim M, Matson ET (2017) A cost-optimization model in multi-agent system routing for drone delivery. Springer, Cham, pp 40–51. https://doi.org/10.1007/978-3-319-60285-1_4

    Google Scholar 

  28. Kuttolamadom M, Mehrabi MG, Weaver J (2010) Design of a stable controller for accurate path tracking of automated guided vehicles systems. Int J Adv Manuf Technol 50(9–12):1183–1188. https://doi.org/10.1007/s00170-010-2569-7

    Article  Google Scholar 

  29. Lee J (2017) Optimization of a modular drone delivery system. In 2017 Annual IEEE International Systems Conference (SysCon) (pp. 1–8). IEEE. doi: https://doi.org/10.1109/SYSCON.2017.7934790

  30. Leno IJ, Sankar SS, Ponnambalam S (2013) An elitist strategy genetic algorithm using simulated annealing algorithm as local search for facility layout design. Int J Adv Manuf Technol:1–13. https://doi.org/10.1007/s00170-013-5519-3

  31. Li J, Chu F, Prins C (2009) Lower and upper bounds for a capacitated plant location problem with multicommodity flow. Comput Oper Res 36(11):3019–3030. Retrieved from http://www.sciencedirect.com/science/article/pii/S0377221713008709. https://doi.org/10.1016/j.cor.2009.01.012

    Article  MathSciNet  MATH  Google Scholar 

  32. Manzour H, Torabi A, Pishvaee MS (2013) New heuristic methods for the single-source capacitated multi facility Weber problem. Int J Adv Manuf Technol 69(5–8):1569–1579. https://doi.org/10.1007/s00170-013-5114-7

    Article  Google Scholar 

  33. Maríc M, Stanimirovíc Z, Milenkovíc N, Djeníc A (2015) Metaheuristic approaches to solving large-scale bilevel uncapacitated facility location problem with clients’ preferences. Yugoslav J Oper Res 25(3):361–378. https://doi.org/10.2298/YJOR130702032M

    Article  MathSciNet  MATH  Google Scholar 

  34. Mohammed F, Idries A, Mohamed N, Al-Jaroodi J, & Jawhar I (2014). UAVs for smart cities: opportunities and challenges. In 2014 International Conference on Unmanned Aircraft Systems (ICUAS) (pp. 267–273). IEEE. doi: https://doi.org/10.1109/ICUAS.2014.6842265

  35. Mourelo Ferrandez S, Harbison T, Weber T, Sturges R, Rich R, Rich R (2016) (JAVIER ARAGON)Optimization of a truck-drone in tandem delivery network using k-means and genetic algorithm. J Ind Eng Manag 9(2):374. https://doi.org/10.3926/jiem.1929

    Google Scholar 

  36. Murray CC, Chu AG (2015) The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery. Transp Res Part C: Emerg Technol 54:86–109. https://doi.org/10.1016/j.trc.2015.03.005

    Article  Google Scholar 

  37. Nikoofal M, Sadjadi S (2010) A robust optimization model for p-median problem with uncertain edge lengths. Int J Adv Manuf Technol 50(1):391–397. https://doi.org/10.1007/s00170-009-2503-z

    Article  Google Scholar 

  38. Owen SH, Daskin MS (1998) Strategic facility location: a review. Eur J Oper Res 111(3):423–447. https://doi.org/10.1016/S0377-2217(98)00186-6

    Article  MATH  Google Scholar 

  39. Özdaǧoǧlu A (2012) A multi-criteria decision-making methodology on the selection of facility location: fuzzy ANP. Int J Adv Manuf Technol 59(5–8):787–803. https://doi.org/10.1007/s00170-011-3505-1

    Google Scholar 

  40. Morgan P (2005) Carbon fibers and their composites. Retrieved October 24, 2017, from https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=P.+Morgan%2C+Carbon+Fibers+and+Their+Composites+%28Materials+Engineering%29.+Boca+Raton%2C+FL%2C+USA%3A+CRC+Press%2C+2005.+&btnG=

  41. Rahman S, Smith DK (2000) Use of location-allocation models in health service development planning in developing nations. Eur J Oper Res 123(3):437–452. https://doi.org/10.1016/S0377-2217(99)00289-1

    Article  MATH  Google Scholar 

  42. Rahmati SHA, Hajipour V, Niaki STA (2013) A soft-computing Pareto-based meta-heuristic algorithm for a multi-objective multi-server facility location problem. Appl Soft Comp J 13(4):1728–1740. https://doi.org/10.1016/j.asoc.2012.12.016

    Article  Google Scholar 

  43. Roy R (1990) A primer on the Taguchi method, competitive manufacturing series. New York

  44. Sabzevari Zadeh A, Sahraeian R, Homayouni SM (2014) A dynamic multi-commodity inventory and facility location problem in steel supply chain network design. Int J Adv Manuf Technol 70(5–8):1267–1282. https://doi.org/10.1007/s00170-013-5358-2

    Article  Google Scholar 

  45. Şahin G, Süral H (2007) A review of hierarchical facility location models. Comput Oper Res Retrieved from http://www.sciencedirect.com/science/article/pii/S0305054805002959 34(8):2310–2331. https://doi.org/10.1016/j.cor.2005.09.005

    Article  MathSciNet  MATH  Google Scholar 

  46. Samarghandi H, Taabayan P, Behroozi M (2013) Metaheuristics for fuzzy dynamic facility layout problem with unequal area constraints and closeness ratings. Int J Adv Manuf Technol 67(9–12):2701–2715. https://doi.org/10.1007/s00170-012-4685-z

    Article  Google Scholar 

  47. Sanjab A, Saad W, & Başar T (2017) Prospect theory for enhanced cyber-physical security of drone delivery systems: a network interdiction game, 0–5. Retrieved from http://arxiv.org/abs/1702.04240

  48. Scott J, & Scott C (2017) Drone delivery models for healthcare. Retrieved from http://scholarspace.manoa.hawaii.edu/handle/10125/41557

  49. Shishebori D, Dayarian I, & Jabbarzadeh A (2014) A new hybrid approach to discrete multiple facility location problem. International Journal of . Retrieved from doi: https://doi.org/10.1007/s00170-013-5337-7, 71, 1-4, 127, 139

  50. Smith C (2015) The surprising facts about who shops online and on mobile. Retrieved July 26, 2017, from https://scholar.google.com/scholar?q=Business insider %28Smith 2015%29&btnG=&hl=en&as_sdt=0%2C5

  51. Srinivasan S, Khan SH (2017) Multi-stage manufacturing/re-manufacturing facility location and allocation model under uncertain demand and return. Int J Adv Manuf Technol:1–14. https://doi.org/10.1007/s00170-017-1066-7

  52. Teixeira JC, Antunes AP (2008) A hierarchical location model for public facility planning. Eur J Oper Res 185(1):92–104. https://doi.org/10.1016/j.ejor.2006.12.027

    Article  MathSciNet  MATH  Google Scholar 

  53. Thiels CA, Aho JM, Zietlow SP, Jenkins DH (2015) Use of unmanned aerial vehicles for medical product transport. Air Med J 34(2):104–108. https://doi.org/10.1016/j.amj.2014.10.011

    Article  Google Scholar 

  54. Troudi A, Addouche S-A, Dellagi S, El Mhamedi A (2017) Logistics support approach for drone delivery fleet. Springer, Cham, pp 86–96. https://doi.org/10.1007/978-3-319-59513-9_9

    Google Scholar 

  55. Vempati L, Crapanzano R, Woodyard C, & Trunkhill C (2017) Linear program and simulation model for aerial package delivery: a case study of Amazon Prime Air in Phoenix, AZ. In 17th AIAA Aviation Technology, Integration, and Operations Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics. doi: https://doi.org/10.2514/6.2017-3936

  56. Welch A (2015) A cost-benefit analysis of Amazon Prime Air. Honors theses. Retrieved from http://scholar.utc.edu/honors-theses/47

  57. Wilson LR (2014) Ethical issues with use of drone aircraft. Proceedings of the IEEE 2014 International symposium on ethics in engineering, science, and technology. IEEE Press. Retrieved from https://dl.acm.org/citation.cfm?id=2960655

  58. Xiang G, Hardy A, Rajeh M, & Venuthurupalli L (2016) Design of the life-ring drone delivery system for rip current rescue. In 2016 I.E. Systems and Information Engineering Design Symposium (SIEDS) (pp. 181–186). IEEE. doi: https://doi.org/10.1109/SIEDS.2016.7489295

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Shavarani, S.M., Nejad, M.G., Rismanchian, F. et al. Application of hierarchical facility location problem for optimization of a drone delivery system: a case study of Amazon prime air in the city of San Francisco. Int J Adv Manuf Technol 95, 3141–3153 (2018). https://doi.org/10.1007/s00170-017-1363-1

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