A new perspective for scheduling the medical resource order and distribution
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- 英文论文题名：A new perspective for scheduling the medical resource order and distribution
- 论文作者：Ming Liu ; Wei Yu
- 英文论文作者：Ming Liu ; Wei Yu ; School of Economics and Management ; Nanjing University of Science and Technology
- 年：2017
- 作者机构：School of Economics and Management,Nanjing University of Science and Technology;
- 英文论文关键词：medical resource ; epidemic diffusion ; scheduling ; optimization ; comparison
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：R197.1
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：5
- 文件大小：357k
- 原文格式：D
- 会议级别：全国
摘要
In our previous works(Liu & Su, 2016a [1], 2016b [2]), we had studied the scheduling of medical resource order and distribution based on an influenza diffusion model. In paper [1], the order size in distribution centers(DCs) was set to be a constant number, and it was improved to be a decision variable in paper [2]. A core decision variable, the number of beds assigned for epidemic patients in each designated hospital at each day, is decided by solving the optimization model in both of these works. This is not suitable for most actual operations because the arrival of patients is totally stochastic. Therefore, this paper provides a new perspective for scheduling the medical resource order and distribution, which considers the arrival of patients in each designated hospital at each day as a stochastic variable. In what follows, we conduct a comprehensive comparison of the new method and the original model in paper [1]. The test results show that the good performance of the new method.
In our previous works(Liu & Su, 2016a [1], 2016b [2]), we had studied the scheduling of medical resource order and distribution based on an influenza diffusion model. In paper [1], the order size in distribution centers(DCs) was set to be a constant number, and it was improved to be a decision variable in paper [2]. A core decision variable, the number of beds assigned for epidemic patients in each designated hospital at each day, is decided by solving the optimization model in both of these works. This is not suitable for most actual operations because the arrival of patients is totally stochastic. Therefore, this paper provides a new perspective for scheduling the medical resource order and distribution, which considers the arrival of patients in each designated hospital at each day as a stochastic variable. In what follows, we conduct a comprehensive comparison of the new method and the original model in paper [1]. The test results show that the good performance of the new method.
In our previous works(Liu & Su, 2016a [1], 2016b [2]), we had studied the scheduling of medical resource order and distribution based on an influenza diffusion model. In paper [1], the order size in distribution centers(DCs) was set to be a constant number, and it was improved to be a decision variable in paper [2]. A core decision variable, the number of beds assigned for epidemic patients in each designated hospital at each day, is decided by solving the optimization model in both of these works. This is not suitable for most actual operations because the arrival of patients is totally stochastic. Therefore, this paper provides a new perspective for scheduling the medical resource order and distribution, which considers the arrival of patients in each designated hospital at each day as a stochastic variable. In what follows, we conduct a comprehensive comparison of the new method and the original model in paper [1]. The test results show that the good performance of the new method.
引文
[1]Liu,M.and WL.Su.A multi-stage scheduling method for medical resource order and distribution based on influenza diffusion model.ICIC Express Letters,Part B:Applications,v 7,n 7,July 1,2016,p 1559-1566.
[2]Liu,M.and WL.Su.An improvement of scheduling method for medical resource order and distribution.Chinese Control Conference,August 26,2016,p 2685-2689.
[3]Enatsu,Y.,Y.Nakata and Y.Muroya,Global stability for a class of discrete SIR epidemic models.Mathematical Biosciences&Engineering Mbe,2010.7(2):p.347-61.
[4]Billard,L.and P.W.A.Dayananda,A multi-stage compartmental model for HIV-infected individuals:I–Waiting time approach.Mathematical Biosciences,2014.249:p.92-101.
[5]Lee,J.,G.Chowell and E.Jung,A dynamic compartmental model for the Middle East respiratory syndrome outbreak in the Republic of Korea:A retrospective analysis on control interventions and superspreading events.Journal of Theoretical Biology,2016.408:p.118-126.
[6]Cui,Q.,et al.,An NSFD scheme for SIR epidemic models of childhood diseases with constant vaccination strategy.Advances in Difference Equations,2014.2014(1):p.1-15.
[7]Liu,Q.,et al.,Asymptotic behavior of a stochastic delayed SEIR epidemic model with nonlinear incidence.Physica A:Statistical Mechanics and its Applications,2016.462:p.870-882.
[8]Alonso-Quesada,S.,M.De la Sen and A.Ibeas,On the discretization and control of an SEIR epidemic model with a periodic impulsive vaccination.Communications in Nonlinear Science and Numerical Simulation,2017.42:p.247-274.
[9]Yarmand,H.,et al.,Optimal two-phase vaccine allocation to geographically different regions under uncertainty.European Journal of Operational Research,2014.233(1):p.208-219.
[10]Nikakhtar,A.and S.M.Hsiang,Incorporating the dynamics of epidemics in simulation models of healthcare systems.Simulation Modelling Practice and Theory,2014.43:p.67-78.
[11]Liu,M.and J.Liang,Dynamic optimization model for allocating medical resources in epidemic controlling.Journal of Industrial Engineering&Management,2013.6(1):p.73-88.
[12]Liu,M.and D.Zhang,A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating.Journal of the Operational Research Society,2016.67(6):p.841-852.
[13]Repoussis,P.P.,et al.,Optimizing emergency preparedness and resource utilization in mass-casualty incidents.European Journal of Operational Research,2016.255(2):p.531-544.
[14]Sung,I.and T.Lee,Optimal allocation of emergency medical resources in a mass casualty incident:Patient prioritization by column generation.European Journal of Operational Research,2016.252(2):p.623-634.
[2]Liu,M.and WL.Su.An improvement of scheduling method for medical resource order and distribution.Chinese Control Conference,August 26,2016,p 2685-2689.
[3]Enatsu,Y.,Y.Nakata and Y.Muroya,Global stability for a class of discrete SIR epidemic models.Mathematical Biosciences&Engineering Mbe,2010.7(2):p.347-61.
[4]Billard,L.and P.W.A.Dayananda,A multi-stage compartmental model for HIV-infected individuals:I–Waiting time approach.Mathematical Biosciences,2014.249:p.92-101.
[5]Lee,J.,G.Chowell and E.Jung,A dynamic compartmental model for the Middle East respiratory syndrome outbreak in the Republic of Korea:A retrospective analysis on control interventions and superspreading events.Journal of Theoretical Biology,2016.408:p.118-126.
[6]Cui,Q.,et al.,An NSFD scheme for SIR epidemic models of childhood diseases with constant vaccination strategy.Advances in Difference Equations,2014.2014(1):p.1-15.
[7]Liu,Q.,et al.,Asymptotic behavior of a stochastic delayed SEIR epidemic model with nonlinear incidence.Physica A:Statistical Mechanics and its Applications,2016.462:p.870-882.
[8]Alonso-Quesada,S.,M.De la Sen and A.Ibeas,On the discretization and control of an SEIR epidemic model with a periodic impulsive vaccination.Communications in Nonlinear Science and Numerical Simulation,2017.42:p.247-274.
[9]Yarmand,H.,et al.,Optimal two-phase vaccine allocation to geographically different regions under uncertainty.European Journal of Operational Research,2014.233(1):p.208-219.
[10]Nikakhtar,A.and S.M.Hsiang,Incorporating the dynamics of epidemics in simulation models of healthcare systems.Simulation Modelling Practice and Theory,2014.43:p.67-78.
[11]Liu,M.and J.Liang,Dynamic optimization model for allocating medical resources in epidemic controlling.Journal of Industrial Engineering&Management,2013.6(1):p.73-88.
[12]Liu,M.and D.Zhang,A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating.Journal of the Operational Research Society,2016.67(6):p.841-852.
[13]Repoussis,P.P.,et al.,Optimizing emergency preparedness and resource utilization in mass-casualty incidents.European Journal of Operational Research,2016.255(2):p.531-544.
[14]Sung,I.and T.Lee,Optimal allocation of emergency medical resources in a mass casualty incident:Patient prioritization by column generation.European Journal of Operational Research,2016.252(2):p.623-634.