Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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A Heuristic for Drone-Utilized Blood Inventory and Delivery Planning

드론 활용 혈액 재고/배송계획 휴리스틱

  • Jang, Jin-Myeong (Graduate School Logistics, Inha University) ;
  • Kim, Hwa-Joong (Graduate School Logistics, Inha University) ;
  • Son, Dong-Hoon (Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology)
  • 장진명 (인하대학교 물류전문대학원) ;
  • 김화중 (인하대학교 물류전문대학원) ;
  • 손동훈 (홍콩과기대학교 토목환경공학과)
  • Received : 2021.08.18
  • Accepted : 2021.09.15
  • Published : 2021.09.30
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Abstract

This paper considers a joint problem for blood inventory planning at hospitals and blood delivery planning from blood centers to hospitals, in order to alleviate the blood service imbalance between big and small hospitals being occurred in practice. The joint problem is to determine delivery timing, delivery quantity, delivery means such as medical drones and legacy blood vehicles, and inventory level to minimize inventory and delivery costs while satisfying hospitals' blood demand over a planning horizon. This problem is formulated as a mixed integer programming model by considering practical constraints such as blood lifespan and drone specification. To solve the problem, this paper employs a Lagrangian relaxation technique and suggests a time efficient Lagrangian heuristic algorithm. The performance of the suggested heuristic is evaluated by conducting computational experiments on randomly-generated problem instances, which are generated by mimicking the real data of Korean Red Cross in Seoul and other reliable sources. The results of computational experiments show that the suggested heuristic obtains near-optimal solutions in a shorter amount of time. In addition, we discuss the effect of changes in the length of blood lifespan, the number of planning periods, the number of hospitals, and drone specifications on the performance of the suggested Lagrangian heuristic.

Keywords

Acknowledgement

This work was supported by Inha University Research Grant.

References

  1. Erickson, M.L., Champion, M.H., Klein, R., Ross, R.L., Neal, Z.M., and Snyder, E.L., Management of blood shortages in a tertiary care academic medical center: The Yale-New Haven Hospital frozen blood reserve, Transfusion, 2008, Vol. 48, No. 10, pp. 2252-2263. https://doi.org/10.1111/j.1537-2995.2008.01816.x
  2. Fisher, M.L., An applications oriented guide to Lagrangian relaxation, Interfaces, 1985, Vol. 15. No. 2, pp. 10-21. https://doi.org/10.1287/inte.15.2.10
  3. Gunpinar, S. and Centeno, G., Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals, Computers & Operations Research, 2015, Vol. 54, pp. 129-141. https://doi.org/10.1016/j.cor.2014.08.017
  4. Haidari, L.A., Brown, S.T., Ferguson, M., Bancroft, E., Spiker, M., Wilcox, A., and Lee, B.Y., The economic and operational value of using drones to transport vaccines, Vaccine, 2016, Vol. 34, No. 34, pp. 4062-4067. https://doi.org/10.1016/j.vaccine.2016.06.022
  5. Huh, J.Y., Lim, Y.A., Hong, Y.J., Kim, K.H., Kim, J.N., Oh, J.A., and Choi, J.K., The experience of applying an Australian red blood cell safety stock calculation to Korean hospitals, The Korean Journal of Blood Transfusion, 2018, Vol. 29, No. 2, pp.140-150. https://doi.org/10.17945/kjbt.2018.29.2.140
  6. Jennings, J.B., Blood bank inventory control, Management Science, 1973, Vol. 19, No. 6, pp. 637-645. https://doi.org/10.1287/mnsc.19.6.637
  7. Kazemi, S.M., Rabbani, M., Tavakkoli-Moghaddam, R., and Shahreza, F.A., Blood inventory-routing problem under uncertainty, Journal of Intelligent & Fuzzy Systems, 2017, Vol. 32, No. 1, pp. 467-481. https://doi.org/10.3233/JIFS-152175
  8. Kim, J., Choi, K.Y., Youn, K.W., Kim, Y., Min, H.K., and Kim, H.O., Requirement of establishment of frozen blood storage system for management of rare blood supply and strategic national stockpile, The Korean Journal of Blood Transfusion, 2018, Vol. 29, No. 1, pp. 3-17. https://doi.org/10.17945/kjbt.2018.29.1.3
  9. Kim, S.J., Lim, G.J., Cho, J., and Cote, M.J., Drone-aided healthcare services for patients with chronic diseases in rural areas, Journal of Intelligent & Robotic Systems, 2017, Vol. 88, No. 1, pp. 163-180. https://doi.org/10.1007/s10846-017-0548-z
  10. Lim, Y., Alterobiotech "Use the freeze protection agent obtained in Antarctica to increase the blood lifespan by six times," Korean Economy Bio Insight, 2020. Lucas, M., Novak, D., and Puranam, K., On the challenges of blood inventory management, Arch Blood Transfusion Disorders, 2018.
  11. Lucas, M., Novak, D., and Puranam, K., On the challenges of blood inventory management, Arch Blood Transfusion Disorders, 2018.
  12. Madan, M.S. and Gilbert, K.C., An exact solution algorithm for a class of production planning and scheduling problems, Journal of the Operational Research Society, 1992, Vol. 43, No. 10, pp. 961-970. https://doi.org/10.2307/2584550
  13. Najafi, M., Ahmadi, A., and Zolfagharinia, H., Blood inventory management in hospitals: Considering supply and demand uncertainty and blood transshipment possibility, Operations Research for Health Care, 2017, Vol. 15, pp. 43-56. https://doi.org/10.1016/j.orhc.2017.08.006
  14. Nedjati, A., Vizvari, B., and Izbirak, G., Post-earthquake response by small UAV helicopters, Natural Hazards, 2016, Vol. 80, No. 3, pp. 1669-1688. https://doi.org/10.1007/s11069-015-2046-6
  15. Oh, D.J., Safety issues and blood supplying hospitals, The Korean Journal of Blood Transfusion, 2015, Special lecture 2, pp. 59-60.
  16. Pulver, A., Wei, R., and Mann, C., Locating AED enabled medical drones to enhance cardiac arrest response times, Prehospital Emergency Care, 2016, Vol. 20, No. 3, pp. 378-389. https://doi.org/10.3109/10903127.2015.1115932
  17. Puranam, K., Novak, D.C., Lucas, M.T., and Fung, M., Managing blood inventory with multiple independent sources of supply, European Journal of Operational Research, 2017, Vol. 259, No. 2, pp. 500-511. https://doi.org/10.1016/j.ejor.2016.11.005
  18. Rajendran, S. and Ravindran, A.R., Inventory management of platelets along blood supply chain to minimize wastage and shortage, Computers & Industrial Engineering, 2019, Vol. 130, pp. 714-730. https://doi.org/10.1016/j.cie.2019.03.010
  19. Raptopoulos, A., Physicaltransport, Talk at Solve for X. 2012.
  20. Salary Guidance Office, Guidance on salary standard revisions, Health Insurance Review & Assessment Service, 2014.
  21. Scott, J. and Scott, C., Drone delivery models for healthcare, In Proceedings of the 50th Hawaii International Conference on System Sciences, 2017. Hawaii, USA, 2017.
  22. Seo, J.-W., Han, K.-S., Comparison of cryopreservation methods of rare red blood cells used for antibody identification tests, The Korean Journal of Blood Transfusion, 2008, Vol. 19, No. 2, pp. 120-131.
  23. Seoul Eastern Blood Center, Bidding announcement for blood transportation services, Korean On-line E-procurement System, 2016.
  24. The Korean Red Cross, 2018 Annual Report on Blood Business Statistics, 2019.
  25. Thiels, C.A., Aho, J.M., Zietlow, S.P., and Jenkins, D.H., Use of unmanned aerial vehicles for medical product transport, Air Medical Journal, 2015, Vol. 34, No. 2, 104-108. https://doi.org/10.1016/j.amj.2014.10.011
  26. Toth, P. and Martello, S., Knapsack problems: Algorithms and computer implementations, Wiley, 1990.
  27. Welch, A., A Cost-benefit Analysis of Amazon Prime Air, University of Tennessee at Chattanooga, 2015.
  28. Zhou, D., Leung, L.C., and Pierskalla, W.P., Inventory management of platelets in hospitals: Optimal inventory policy for perishable products with regular and optional expedited replenishments, Manufacturing & Service Operations Management, 2011, Vol. 13, No. 4, pp. 420-438. https://doi.org/10.1287/msom.1110.0334