Platelet ordering policies at hospitals using stochastic integer programming model and heuristic approaches to reduce wastage

[Display omitted] •Hospitals waste a significant amount of blood platelets due to demand uncertainty.•Stochastic integer programming model is developed to determine ordering policy.•Model is computationally complex and hence three heuristic policies are proposed.•Best policies for several cost, dema...

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Vydané v:Computers & industrial engineering Ročník 110; s. 151 - 164
Hlavní autori: Rajendran, Suchithra, Ravindran, A. Ravi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.08.2017
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ISSN:0360-8352
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Abstract [Display omitted] •Hospitals waste a significant amount of blood platelets due to demand uncertainty.•Stochastic integer programming model is developed to determine ordering policy.•Model is computationally complex and hence three heuristic policies are proposed.•Best policies for several cost, demand and shelf life settings are identified.•Hospital management can decide most suitable policy for its administration settings. Demand uncertainty coupled with a short shelf life of blood platelets has led to a significant wastage at hospitals. An important objective is to minimize wastage of platelets while maintaining a specified service level. To achieve this objective, a mixed integer stochastic programming model under demand uncertainty is developed. Due to the computational complexity of the problem, three heuristic rules are proposed for determining the platelet ordering policy at the hospital. The performance of these three ordering policies is compared against that of the periodic review order-up-to policy proposed in the literature using real-life data obtained from a medical center. The shelf life of arriving platelets, coefficient of variation of demand and cost parameters are varied, and their impact is analyzed on the performance measures and the best rule with respect to each setting is determined. Based on the shelf life setting and cost prioritization, the decision maker can choose the most suitable rule for the hospital.
AbstractList [Display omitted] •Hospitals waste a significant amount of blood platelets due to demand uncertainty.•Stochastic integer programming model is developed to determine ordering policy.•Model is computationally complex and hence three heuristic policies are proposed.•Best policies for several cost, demand and shelf life settings are identified.•Hospital management can decide most suitable policy for its administration settings. Demand uncertainty coupled with a short shelf life of blood platelets has led to a significant wastage at hospitals. An important objective is to minimize wastage of platelets while maintaining a specified service level. To achieve this objective, a mixed integer stochastic programming model under demand uncertainty is developed. Due to the computational complexity of the problem, three heuristic rules are proposed for determining the platelet ordering policy at the hospital. The performance of these three ordering policies is compared against that of the periodic review order-up-to policy proposed in the literature using real-life data obtained from a medical center. The shelf life of arriving platelets, coefficient of variation of demand and cost parameters are varied, and their impact is analyzed on the performance measures and the best rule with respect to each setting is determined. Based on the shelf life setting and cost prioritization, the decision maker can choose the most suitable rule for the hospital.
Author Rajendran, Suchithra
Ravindran, A. Ravi
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Keywords Platelet
Wastage
Heuristic ordering policies
Stochastic integer programming
Language English
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Snippet [Display omitted] •Hospitals waste a significant amount of blood platelets due to demand uncertainty.•Stochastic integer programming model is developed to...
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StartPage 151
SubjectTerms Heuristic ordering policies
Platelet
Stochastic integer programming
Wastage
Title Platelet ordering policies at hospitals using stochastic integer programming model and heuristic approaches to reduce wastage
URI https://dx.doi.org/10.1016/j.cie.2017.05.021
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