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Dispatching medical supplies in emergency events via uncertain programming

Author

Listed:
  • Hui Li

    (Hubei University)

  • Jin Peng

    (Huanggang Normal University)

  • Shengguo Li

    (Huanggang Normal University)

  • Chuang Su

    (Shanghai Normal University)

Abstract

This paper employs uncertain programming to deal with a problem of dispatching medical supplies in emergency events. As we know, the highly unpredictable nature of emergencies and the severity of the accident may lead to uncertainty both in demands and running times. Under this condition, the demands and running times are supposed to be uncertain variables. Within the framework of uncertain programming, two mathematical models are constructed. In addition, some properties of the models are also discussed. Moreover, a hybrid intelligent algorithm for solving the proposed models in general cases is designed. Finally, some numerical examples are also presented to illustrate the optimization ideas and the effectiveness of the proposed algorithm.

Suggested Citation

  • Hui Li & Jin Peng & Shengguo Li & Chuang Su, 2017. "Dispatching medical supplies in emergency events via uncertain programming," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 549-558, March.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:3:d:10.1007_s10845-014-1008-2
    DOI: 10.1007/s10845-014-1008-2
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    References listed on IDEAS

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    1. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    2. Beraldi, P. & Bruni, M. E. & Conforti, D., 2004. "Designing robust emergency medical service via stochastic programming," European Journal of Operational Research, Elsevier, vol. 158(1), pages 183-193, October.
    3. Armann Ingolfsson & Susan Budge & Erhan Erkut, 2008. "Optimal ambulance location with random delays and travel times," Health Care Management Science, Springer, vol. 11(3), pages 262-274, September.
    4. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    5. G Barbarosoǧlu & Y Arda, 2004. "A two-stage stochastic programming framework for transportation planning in disaster response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(1), pages 43-53, January.
    6. Chang, Mei-Shiang & Tseng, Ya-Ling & Chen, Jing-Wen, 2007. "A scenario planning approach for the flood emergency logistics preparation problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 737-754, November.
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    Cited by:

    1. Lin Chen & Ting Dong & Jin Peng & Dan Ralescu, 2023. "Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review," Mathematics, MDPI, vol. 11(11), pages 1-45, May.
    2. Merve Cengiz Toklu, 2023. "A fuzzy multi-criteria approach based on Clarke and Wright savings algorithm for vehicle routing problem in humanitarian aid distribution," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2241-2261, June.

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