Integrated planning for blood platelet production: a robust optimization approach

Document Type : Research Paper

Authors

1 School of Industrial Engineering, Iran University of Science & Technology

2 School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran

3 School of Industrial Engineering, Iran University of Science &Technology

Abstract

Perishability of blood products as well as uncertainty in demand amounts complicate the management of blood supply for blood centers. This paper addresses a mixed-integer linear programming model for blood platelets production planning while integrating the processes of blood collection as well as production/testing, inventory control and distribution. Whole blood-derived production methods for blood platelets (i.e., buffy coat and platelet-rich plasma methods) are particularly focused in our research. The problem is tackled with the aim of minimizing the supply chain total cost. To capture inherent uncertainty of input data, a robust programming approach is devised. A set of numerical experiments is carried out to evaluate the performance of the proposed model and the solution technique. Thereto, we employ two criteria: the mean and standard deviation of constraint violations under a number of random realizations to measure the quality of solutions achieved by both the proposed deterministic and robust models. Finally, several sensitivity analyses are accomplished to provide valuable managerial insights. The results imply the domination of robust approach over the deterministic one.

Keywords

Main Subjects

References

-          Abdulwahab U., & Wahab, M. (2014). Approximate dynamic programming modeling for a typical blood platelet bank. Computers & Industrial Engineering, 78, 259-270.
-          Arvan, M., Tavakkoli-Moghaddam, R., & Abdollahi, M. (2015). Designing a bi-objective, multi-product supply chain network for blood supply. Uncertain Supply Chain Management, 3, 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.
-          Ben-Tal, A., & Nemirovski, A. (1999). Robust solutions of uncertain linear programs. Operations research letters, 25(1), 1-13.‏   
-          Ben-Tal, A., & Nemirovski, A. (2000). Robust solutions of linear programming problems contaminated with uncertain data. Mathematical programming, 88(3), 411-424.‏
-          Ben-Tal, A., & Nemirovski, A. (2002). Robust optimization–methodology and applications. Mathematical Programming, 92(3), 453-480.‏
-          Bertolini F., Rebulla P., Porretti L., & Murphy S. (1992). Platelet quality after 15-day storage of platelet concentrates prepared from buffy coats and stored in a glucose-free crystalloid medium. Transfusion, 32, 9–16.
-          Bertsimas, D., & Sim, M. (2003). Robust discrete optimization and network flows. Mathematical programming, 98(1-3), 49-71. ‏
-          Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations research, 52(1), 35-53.‏
-          Brandeau M. L., Sainfort, F., & Pierskalla, W.  P. (2004). Operations research and Health Care: a Handbook of methods and applications. Springer Science & Business Media, 70.
-          Deuermeyer, B. L., Pierskalla, W. P. (1978) .A By-Product Production System with an Alternative. Management Science, 24(13), 1373-1383.
-          Drackley, A., Newbold, K. B., Paez, A. & Heddle, N. (2012). Forecasting Ontario's blood supply and demand, Transfusion, 52(2), 366-374.
-          Duan, Q., & Liao, T. W. (2014). Optimization of blood supply chain with shortened shelf lives and ABO compatibility. International Journal of Production Economics, 153, 113-129.‏
-          Fischetti, M., & Monaci, M. (2009). Light robustness. In Robust and online large-scale optimization, Springer Science & Business Media, 61-84. ‏
-          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.
-          Haijema, R., Van Der Wal, J., & Van Dijk, N. M. (2007). Blood platelet production: Optimization by dynamic programming and simulation. Computers & Operations Research, 34, 760-779.
-          Haijema, R., Van Der Wal, J., & Sibinga, C. S. (2009). Blood platelet production with breaks: Optimization by SDP and simulation. International Journal of Production Economics, 121,464-473.
-          Jokar, A., & Hosseini-Motlagh, S. M. (2015). Impact of Capacity of Mobile Units on Blood Supply Chain Performance: Results from a Robust Analysis. International Journal of Hospital Research, 4(3), 109-114.‏  
-          Kaiser Health News, 2015. http://www.kaiserhealthnews.org/Daily-Reports/2012/June/13/health-care-costs.aspx [accessed 01.05.16].
-          Levin, E., Culibrk,B., Gyöngyössy-Issa, M., Weiss, S., Scammell, K., LeFresne, W., Jenkins, C., & Devine, D. V. (2008). Implementation of buffy coat platelet component production: comparison to platelet-rich plasma platelet production. Transfusion, 48(11), 2331-2337.
-          Nagurney, A., Masoumi, A., & Yu, M. (2012). Supply chain network operations management of a blood banking system with cost and risk minimization. Computational Management Science, 9, 205-231.
-          Rastegar-Panah, M. M., Hosseini-Motlagh, S. M., Babaei, E., and Noughani, F. (2013). Use and usefulness of social network analysis in the primary health context. International Journal of Hospital Research, 2(4), 177-186.
-          Riahi, N., Hosseini-Motlagh, S. M., & Teimourpour, B.  A. (2013). Three-phase Hybrid Times Series Modeling Framework for Improved Hospital Inventory Demand Forecast. International Journal of Hospital Research, 2(3), 133-142.
-          Schreiber, G. B., Schlumpf, K. S., Glynn, S. A., Wright, D. J. , Tu, Y., King, M. R., Higgins, M. J., Kessler, D., Gilcher, R., Nass, C. C., Guiltinan, A. M., and L. B. I. R. E. D. S. (2006). National Heart, "Convenience, the bane of our existence, and other barriers to donating," Transfusion, 46, 545-553.
-          Singh, C. (1982). Convex programming with set-inclusive constraints and its applications to generalized linear and fractional programming. Journal of Optimization Theory and Applications, 38(1), 33-42.‏
-          Soleimany Ferizhandy, A. (2011). Platelet activation of platelet concentrates derived from buffy coat and apheresis methods. Transfusion and Apheresis Science, 44, 11–13.
-          The World Bank, 2015. <http://data.worldbank.org/indicator/SH.XPD.TOTL.ZS> [accessed 01.05.16].
-          Tofighi, S., Torabi, S. A., & Mansouri, S. A. (2016). Humanitarian logistics network design under mixed uncertainty. European Journal of Operational Research, 250(1), 239-250.‏
-          Van Dijk, N., Haijema, R. Van Der Wal, J., & Sibinga, C. S. (2009). Blood platelet production: a novel approach for practical optimization. Transfusion, 49, 411-420.
-          Vassallo, R. R., & Murphy, S. (2006). A critical comparison of platelet preparation methods. Current Opinion in Hematology, 13(5), 323-330.
-          Zahiri, B., Torabi, S. A., Mousazadeh, M., & Mansouri, S. A. (2015). Blood collection management: Methodology and application. Applied Mathematical Modelling, 39(23), 7680-7696.‏

Files

History

  • Receive Date: 19 December 2016
  • Revise Date: 09 February 2017
  • Accept Date: 18 February 2017

Share

How to cite

Statistics