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Three-Level and Dynamic Optimization Model for Allocating Medical Resources Based on Epidemic Diffusion Model

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LISS 2012

Abstract

In this paper, a three-level and dynamic linear programming model for allocating medical resources based on epidemic diffusion model is proposed. The epidemic diffusion model is used to construct the forecasting mechanism for dynamic demand of medical resources. Heuristic algorithm coupled with MTLAB mathematical programming solver is adopted to solve the model. A numerical example is presented for testing the model’s practical applicability. The result may provide some guidelines for decision-makers who are in charge of medical resources allocation in an epidemics control effort.

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Acknowledgments

This work has been partially supported by the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No. 11YJCZH109), and the project in Nanjing University of Science and Technology (2011YBXM96), (2011XQTR10), (AE88072) and (JGQN1102). The authors wish to thank Prof. Ding Zhang from State University of New York (USA), who read earlier versions of this paper. His helpful suggestions improved the presentation significantly.

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Authors and Affiliations

  1. Department of Management Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, 210094, P.R. China

    Ming Liu & Peiyong Zhang

Authors
  1. Ming Liu
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  2. Peiyong Zhang
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Correspondence to Ming Liu .

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Editors and Affiliations

  1. Beijing Jiaotong University, Beijing, 100044, China, People's Republic

    Zhenji Zhang

  2. , Department of information Management, Beijing Jiaotong University, 3 Shangyuancun, Xizhimenwai, Beijing, 100044, China, People's Republic

    Runtong Zhang

  3. , School of Economics and Management, Beijing Jiaotong University, Haidian District, Beijing, 100044, China, People's Republic

    Juliang Zhang

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Liu, M., Zhang, P. (2013). Three-Level and Dynamic Optimization Model for Allocating Medical Resources Based on Epidemic Diffusion Model. In: Zhang, Z., Zhang, R., Zhang, J. (eds) LISS 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32054-5_36

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