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Stochastic facility location model for drones considering uncertain flight distance

  • S.I. : Applications of OR in Disaster Relief Operations, Part II
  • Published:
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Abstract

This paper developed a stochastic modelling framework to determine the locations and transport capacities of drone facilities for effectively coping with a disaster. The developed model is applicable to emergency planning that incorporates drones into humanitarian logistics while taking into account the uncertain characteristics of drone operating conditions. Because of the importance of speedy decision making in disaster management, a heuristic algorithm was developed using Benders decomposition, which generates time-efficient high-quality solutions. The linear programming rounding method was used to make the algorithm efficient. Computational experiments demonstrated the superiority of the developed algorithm, and a sensitivity analysis was carried out to gain additional insights.

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Acknowledgements

The authors are grateful for the valuable comments from anonymous reviewers. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science, ICT and Future Planning (MSIT) [NRF-2017R1A2B2007812]; the Basic Science Research Program through the NRF funded by the Ministry of Education (NRF-2015R1D1A1A01057719).

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  1. Department of Industrial Engineering and Institute for Industrial Systems Innovation, Seoul National University, Seoul, 08826, Korea

    Dongwook Kim, Kyungsik Lee & Ilkyeong Moon

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  1. Dongwook Kim
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  2. Kyungsik Lee
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  3. Ilkyeong Moon
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Correspondence to Ilkyeong Moon.

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Kim, D., Lee, K. & Moon, I. Stochastic facility location model for drones considering uncertain flight distance. Ann Oper Res 283, 1283–1302 (2019). https://doi.org/10.1007/s10479-018-3114-6

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  • DOI: https://doi.org/10.1007/s10479-018-3114-6

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