A DSS to manage platelet production supply chain for regional blood centers

Ghandforoush, Parviz; Sen, Tarun K.

doi:10.1016/j.dss.2010.06.005

Cited by 110 publications

(45 citation statements)

References 27 publications

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“…[19]), the health care sector (see e.g. [13,22]), and facility location in the health care sector [21] is not at all new. However, due to several specificities in organ transplants, our model is more complex than a classical facility location model (see, e.g., [8]).…”

Section: Introductionmentioning

confidence: 99%

Optimizing the facility location design of organ transplant centers

Beliën¹,

Boeck²,

Colpaert³

et al. 2013

Decision Support Systems

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a b s t r a c t a r t i c l e i n f o Available online xxxx Keywords:Facility location Organ transplant Long-term planning Mixed integer linear programming This paper presents a mixed integer linear programming (MILP) long-term decision model to optimize the location of organ transplant centers. The objective is to minimize the sum of the weighted time components between the moment a donor organ becomes available and its transplantation into the recipient's body. The weight factor for the elapsed time before the organ's removal from the donor body allows to assign a lower weight to this time component in the objective function in order to reflect the criticality of the process after the organ's removal. The specificity of organ transplants makes the model more complex than a traditional facility location model. The model is applied to the Belgian organ transplant path. Extensive numerical experiments reveal the key factors that impact the long-term decision of centralizing versus decentralizing transplant centers.

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Section: Introductionmentioning

confidence: 99%

Optimizing the facility location design of organ transplant centers

Beliën¹,

Boeck²,

Colpaert³

et al. 2013

Decision Support Systems

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“…There are two ways to derive platelets; the first way is using a centrifuge to separate the platelet rich plasma from whole blood called random platelet and the second way is to use apheresis tool. In case of random platelet production, whole blood of donated should be transported periodically due to 6 hours limit on separation from red blood cell (Ghandforoush et al, 2010). The aforementioned characteristics of platelets have intensified the existing complexities of blood supply chain.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…The analyses resulted in lower platelet outdate. Ghandforoush et al (2010) also addressed platelet supply chain problem. They proposed an integer model for scheduling of whole blood transportation from bloodmobiles to blood center intended for platelet separation purposes.…”

Section: Introductionmentioning

confidence: 99%

Solving a bi-objective mathematical programming model for bloodmobiles location routing problem

Rabbani¹,

Aghabegloo²,

Farrokhi-Asl³

2017

10.5267/j.ijiec

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Perishability of platelets, uncertainty of donors' arrival and conflicting views in platelet supply chain have made platelet supply chain planning a problematic issue. In this paper, mobile blood collection system for platelet production is investigated. Two mathematical models are presented to cover the bloodmobile collection planning problem. The first model is a multi-objective fuzzy mathematical programming in which the bloodmobiles locations are considered with the aim of maximizing potential amount of blood collection and minimizing the operational cost. The second model is a vehicle routing problem with time windows which studies the shuttles routing problem. To tackle the first model, it is reformulated as a crisp multi objective linear programming model and then solved through a fuzzy multi objective programming approach. Several sensitivity analysis are conducted on important parameters to demonstrate the applicability of the proposed model. The proposed model is then solved by using a tailored Simulated Annealing (SA) algorithm. The numerical results demonstrate promising efficiency of the proposed solution method.

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“…Madden et al [11] evaluate the impact of two different collection methods for RBCs, using fractionation and double red blood cells donation by apheresis (2RBC) (fractionation produces just one unit of RBCs while 2RBC produces two units). Ghandforoush and Sen [12] use a nonlinear integer program to support the daily process of platelet production planning. Finally, Gunpinar [13] minimizes the distance of collecting blood units from remote donors.…”

Section: Collection Stagementioning

confidence: 99%

Simulation-optimization model for production planning in the blood supply chain

Osorio

Brailsford

Smith

et al. 2016

Health Care Manag Sci

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Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

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A DSS to manage platelet production supply chain for regional blood centers

Cited by 110 publications

References 27 publications

Optimizing the facility location design of organ transplant centers

Optimizing the facility location design of organ transplant centers

Solving a bi-objective mathematical programming model for bloodmobiles location routing problem

Simulation-optimization model for production planning in the blood supply chain

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