عنوان مقاله [English]
نویسندگان [English]چکیده [English]
There are issues such as limitation of blood resources, perishability, special preservation conditions of blood products and high wastage and shortage costs of blood products, make management of blood products consumption as one of the most complex issues in healthcare systems. This paper proposes a linear mathematical model to optimize consumption of the blood products in hospitals. In the proposed model, in addition to distribution of blood products between hospitals by blood center, possibility of lateral transshipments between hospitals considered as a strategy to deal with demand uncertainty. Furthermore, factor of blood freshness and the need of some surgeries for fresh blood considered in this model as real conditions. Finally, to validate the proposed model, a case related to one blood center and eight hospitals in Tehran city presented and its results discussed
Alfonso, E., Augusto, V., & Xie, X. (2015). Mathematical programming models for annual and weekly bloodmobile collection planning. IEEE Transactions on Automation Science and Engineering, 12(1), 96-105.
Arvan, M., Tavakkoli-Moghaddam, R., & Abdollahi, M. (2015). Designing a bi-objective and multi-product supply chain network for the supply of blood. Uncertain Supply Chain Management, 3(1), 57-68.
Beliën, J., & Forcé, H. (2012). Supply chain management of blood products: A literature review. European Journal of Operational Research, 217(1), 1-16.
Cohen, M. A., & Pierskalla, W. P. (1975). Management policies for a regional blood bank. Transfusion, 15(1), 58-67.
Fontaine, M. J., Chung, Y. T., Erhun, F., & Goodnough, L. T. (2010). Age of blood as a limitation for transfusion: potential impact on blood inventory and availability. Transfusion, 50(10), 2233-2239.
Ghandforoush, P., & Sen, T. K. (2010). A DSS to manage platelet production supply chain for regional blood centers. Decision Support Systems, 50(1), 32-42.
Gunpinar, S., & Centeno, G. (2015). Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals. Computers & Operations Research, 54, 129-141.
Gunpinar, S. (2013). Supply chain optimization of blood products. University of South Florida, Scholar Commons.
Haijema, R., van der Wal, J., & van Dijk, N. M. (2007). Blood platelet production: Optimization by dynamic programming and simulation. Computers & Operations Research, 34(3), 760-779.
Hemmelmayr, V., Doerner, K. F., Hartl, R. F., & Savelsbergh, M. W. (2009). Delivery strategies for blood products supplies. OR spectrum, 31(4), 707-725.
Hemmelmayr, V., Doerner, K. F., Hartl, R. F., & Savelsbergh, M. W. (2010). Vendor managed inventory for environments with stochastic product usage. European Journal of Operational Research, 202(3), 686-695.
Hosseinifard, Z., & Abbasi, B. (2016). The inventory centralization impacts on sustainability of the blood supply chain. Computers & Operations Research.
Nahmias, S. (1982). Perishable inventory theory: A review. Operations research, 30(4), 680-708.
Osorio, A. F., Brailsford, S. C., & Smith, H. K. (2015). A structured review of quantitative models in the blood supply chain: a taxonomic framework for decision-making. International Journal of Production Research, 53(24), 7191-7212.
Pegels, C. C., & Jelmert, A. E. (1970). An evaluation of blood-inventory policies: A Markov chain application. Operations Research, 18(6), 1087-1098.
Pierskalla, W. P., & Roach, C. D. (1972). Optimal issuing policies for perishable inventory. Management Science, 18(11), 603-614.
Pierskalla, W. P. (2005). Supply chain management of blood banks. In Operations research and health care (pp. 103-145). Springer US.
Prastacos, G. P. (1978). Optimal myopic allocation of a product with fixed lifetime. Journal of the operational Research Society, 29(9), 905-913.
Prastacos, G. P., & Brodheim, E. (1980). PBDS: a decision support system for regional blood management. Management Science, 26(5), 451-463.
Prastacos, G. P. (1981). Allocation of a perishable product inventory. Operations Research, 29(1), 95-107.
Sapountzis, C. (1985). Analytical Evaluation of the Characteristic Curve of a Blood Bank and Its Usefulness in Blood Banking. European Journal of Operational Research, 19 (1): 20–32.
Silva Filho, O. S., Carvalho, M. A., Cezarino, W., Silva, R., & Salviano, G. (2013). Demand forecasting for blood components distribution of a blood supply chain. IFAC Proceedings Volumes, 46(24), 565-571.
Sherali, H. D., & Alameddine, A. (1992). A new reformulation-linearization technique for bilinear programming problems. Journal of Global optimization, 2(4), 379-410.
Van Dijk, N., Haijema, R., Van Der Wal, J., & Sibinga, C. S. (2009). Blood platelet production: a novel approach for practical optimization. Transfusion, 49(3), 411-420.
Yahnke, D. P., Rimm, A. A., Makowski, G. G., & Aster, R. H. (1973). Analysis and Optimization of a Regional Blood Bank Distribution Process: II. Derivation and Use of a Method for Evaluating Hospital Management Procedures. Transfusion, 13(3), 156-169.