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Multiple ground/aerial parcel delivery problem: a Weighted Road Network Voronoi Diagram based approach

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Abstract

The Multiple Ground/Aerial Parcel Delivery Problem (MGAPDP), an extension of the Ground/Aerial Parcel Delivery Problem (GAPDP), aims to find an optimal partition that minimizes the overall delivery time of all trucks by serving all destinations once and returning to the distribution center. This paper presents two heuristic solutions to the MGAPDP based on the Weighted Road Network Voronoi Diagram, i.e., Multiplicatively Weighted Road Network Voronoi Diagram (MRVD) and Additively Weighted Road Network Voronoi Diagram (ARVD). In our proposed problem, we assume that trucks travel on road networks, and UAVs move in Euclidean spaces and can be launched at any locations on roads. Each truck is equipped with a UAV, and each UAV can only be operated in Visual-Line-Of-Sight (VLOS) areas. When only one truck is considered, an intuitive approach is to check all possible locations on roads in the VLOS areas and find a globally optimal location for every destination if UAVs are used for delivery. As for multiple trucks, all of the partitions of destinations have to be considered. To avoid high computational cost for multiple truck/UAV pairs, the Weighted Road Network Voronoi Diagram is utilized to form the delivery group for each truck/UAV pair. All of the results are evaluated through extensive experiments, and the results indicate that, while both heuristic solutions effectively reduce the delivery time especially when the number of truck/UAV pairs is low, ARVD has exhibited a lower delivery time than MRVD in the majority of the considered scenarios.

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References

  1. Administration, F.A.: Summary of Small Unmanned Aircraft Rule (Part 107). https://www.faa.gov/uas/media/Part_107_Summary.pdf

  2. Agatz, N., Bouman, P., Schmidt, M.: Optimization approaches for the traveling salesman problem with drone. ERIM Report Series (2016)

  3. Amazon.com, I.: Amazon Prime Air. https://www.amazon.com/Amazon-Prime-Air/b?ie=UTF8&node=8037720011. Accessed 1 May 2019

  4. Brinkhoff, T.: A framework for generating network-based moving objects. GeoInformatica 6(2), 153–180 (2002)

    Article  MATH  Google Scholar 

  5. de Freitas, J.C., Penna, P.H.V.: A randomized variable neighborhood descent heuristic to solve the flying sidekick traveling salesman problem. Electron. Notes Discret. Math. 66, 95–102 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  6. Dorling, K., Heinrichs, J., Messier, G.G., Magierowski, S.: Vehicle routing problems for drone delivery. IEEE Trans. Sys. Man Cybern 47(1), 70–85 (2017)

    Article  Google Scholar 

  7. Ferrandez, S.M., Harbison, T., Weber, T., Sturges, R., Rich, R.: Optimization of a truck-drone in tandem delivery network using k-means and genetic algorithm. J. Ind. Eng. Manag. 9(2), 374–388 (2016)

    Google Scholar 

  8. Gavalas, D., Konstantopoulos, C., Mastakas, K., Pantziou, G.: A survey on algorithmic approaches for solving tourist trip design problems. J. Heuristics 20(3), 291–328 (2014)

    Article  Google Scholar 

  9. Google, I.: Project Wing. http://www.bbc.com/news/technology-28964260 (2019). Accessed 1 May 2019

  10. Group, D.P.D.: http://www.dhl.com/en/press/releases/releases_2014/group/dhl_parcelcopter_launches_initial_operations_for_research_purposes.html (2019). Accessed 1 May 2019

  11. Ha, Q.M., Deville, Y., Pham, Q.D., Heuristic, M.H. Hà.: methods for the Traveling Salesman Problem with Drone. https://pdfs.semanticscholar.org/59b4/8e77e710917d85facb5d2cebf2e2ebd5dfae.pdf (2015). Accessed 1 May 2019

  12. Held, M., Karp, R.M.: A dynamic programming approach to sequencing problems. J. Soc. Ind. Appl. Math. 10(1), 196–210 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  13. Hernández-Pérez, H., Rodríguez-Martín, I., Salazar-González, J.-J.: A hybrid heuristic approach for the multi-commodity pickup-and-delivery traveling salesman problem. Eur. J. Oper. Res. 251(1), 44–52 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  14. Hoffman, K.L., Padberg, M., Rinaldi, G.: Traveling salesman problem. In: Encyclopedia of Operations Research and Management Science, pp. 1573–1578 (2013)

  15. Hosseinabadi, A.A., Kardgar, M., Shojafar, M., Shamshirband, S., Abraham, A.: Gels-ga: hybrid metaheuristic algorithm for solving multiple travelling salesman problem. In: ISDA, pp. 76–81 (2014)

  16. Jones, J., Adamatzky, A.: Computation of the travelling salesman problem by a shrinking blob. Natural Comput. 13(1), 1–16 (2014)

    Article  MathSciNet  Google Scholar 

  17. Ku, W.-S., Zimmermann, R.: Location-based spatial queries with data sharing in mobile environments. In: 22nd International Conference on Data Engineering Workshops (ICDEW’06), p. x140 (2006)

  18. Ku, W.-S., Zimmermann, R.: Nearest neighbor queries with peer-to-peer data sharing in mobile environments. Pervas. Mob. Comput. 4(5), 775–788 (2008)

    Article  Google Scholar 

  19. Murray, C.C., Chu, A.G.: The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery. Transp. Res. Part C 54, 86–109 (2015)

    Article  Google Scholar 

  20. Papadimitriou, C.H.: The Euclidean travelling salesman problem is NP-complete. Theoret. Comput. Sci. 4(3), 237–244 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  21. Wang, X., Poikonen, S., Golden, B.: The vehicle routing problem with drones: several worst-case results. In:Optimization Letters, pp. 1–19 (2016)

  22. Xu, X., Yuan, H., Liptrott, M., Trovati, M.: Two phase heuristic algorithm for the multiple-travelling salesman problem. Soft Comput. 1–15 (2017)

  23. Zhang, J., Shen, T., Wang, W., Jiang, X., Ku, W., Sun, M., Chiang, Y.: A VLOS compliance solution to ground/aerial parcel delivery problem. In: 2019 20th IEEE International Conference on Mobile Data Management (MDM), Hong Kong, Hong Kong, pp. 201–209 (2019)

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Funding

Funding was provided by National Science Foundation.

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Authors and Affiliations

  1. Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA

    Po-wei Harn, Ji Zhang, Ting Shen, Wenlu Wang & Wei-Shinn Ku

  2. Department of Computer Science, Earlham College, Richmond, IN, USA

    Xunfei Jiang

  3. Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan, ROC

    Min-Te Sun

  4. Spatial Sciences Institute, University of Southern California, Los Angeles, CA, USA

    Yao-Yi Chiang

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  1. Po-wei Harn
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  2. Ji Zhang
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Correspondence to Wei-Shinn Ku.

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Harn, Pw., Zhang, J., Shen, T. et al. Multiple ground/aerial parcel delivery problem: a Weighted Road Network Voronoi Diagram based approach. Distrib Parallel Databases 41, 549–569 (2023). https://doi.org/10.1007/s10619-021-07347-w

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