It is in the April 2012 issue of Computational Management Science and is in a special issue edited by Professor Georg Pflug.
In this paper, we focus on a specific perishable product – that of human blood – and the optimization of a blood banking network system. Nahmias (1982) claimed that: “The interest among researchers in perishable inventory problems has been sparked primarily by problems of blood bank management. Some of the possible reasons for this interest might be that blood bank research has been supported by public funds.” Prastacos (1984) provided a review, to that date, of blood inventory management, from both theoretical and practical perspectives. Whether or not Nahmias’ statement is still valid – considering all the recent concerns about the safety of perishable products, blood bank management from a supply chain network perspective merits a fresh and updated approach.
This topic is especially timely today, since it has been reported that the number of disasters and the number of people affected by disasters has been growing over the past decade and blood is certainly a life-saving product (cf. Nagurney and Qiang (2009)). Blood service operations are a key component of the healthcare system all over the world. According to the American Red Cross, over 39,000 donations are needed everyday in the United States, alone, and the blood supply is frequently reported to be just 2 days away from running out. Of 1,700 hospitals participating in a survey in 2007, a total of 492 reported cancellations of elective surgeries on one or more days due to blood shortages. While for many hospitals, the reported number of blood-related delays was not significant, hospitals with as many days of surgical delays as 50 or even 120 have been observed. Furthermore, in 2006, the national estimate for the number of units of whole blood and all components outdated by blood centers and hospitals was 1,276,000 out of 15,688,000 units (Whitaker et al. (2007)). Considering also the ever-increasing hospital cost of a unit of red blood cells with a 6.4% increase from 2005 to 2007 further highlights the criticality of this perishable, lifesaving product.
In the US, this criticality has become more of an issue in the Northeastern and Southwestern states since this cost is meaningfully higher compared to that of the Southeastern and Central states. Moreover, hospitals were responsible for approximately 90% of the outdates, with this volume of medical waste imposing discarding costs to the already financially-stressed hospitals (The New York Times (2010)).
In this paper, we developed a generalized network optimization model for the complex supply chain of human blood, which is a life-saving, perishable product. In particular, we considered a regionalized blood banking system consisting of collection sites, testing and processing facilities, storage facilities, distribution centers, as well as points of demand, which, typically, include hospitals.
Our multicriteria system-optimization approach on generalized networks with arc multipliers captures many of the critical issues associated with blood supply chains such as the determination of the optimal allocations, and the induced supply-side risk, as well as the induced cost of discarding the waste, while satisfying the uncertain demands as closely as possible.
The framework that we present in this paper is also applicable, with appropriate modifications, to the
optimization of other supply chains of perishable products.
The complete analysis, along with references, can be found in our paper.
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