Approximate dynamic programming modeling for a typical blood platelet bank

Computers and Industrial Engineering

Volumn 78, Issue , 2014, Pages 259-270

  Abdulwahab, U ^a   Wahab, M I M ^a  

^a RYERSON UNIVERSITY   (Canada)

Author keywords

Approximate dynamic programming; Blood bank; Blood platelet; Health care management; Inventory management; Inventory model; News vendor; Perishable product; Resource allocation; Supply chain

Indexed keywords

DROPS; INVENTORY CONTROL; PLATELETS; RESOURCE ALLOCATION; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; SUPPLY CHAIN MANAGEMENT; SUPPLY CHAINS;

APPROXIMATE DYNAMIC PROGRAMMING; BLOOD BANK; BLOOD PLATELETS; HEALTH-CARE MANAGEMENTS; INVENTORY MANAGEMENT; INVENTORY MODELING; NEWS-VENDOR; PERISHABLE PRODUCT;

DYNAMIC PROGRAMMING;

EID: 84912080708     PISSN: 03608352     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cie.2014.07.017     Document Type: Article

References (39)

1. Abdulwahab, U., & Wahab, M. I. M. (2013). Approximate dynamic programming modeling for a typical blood platelet bank. Oriental Journal of Computer Science and Technology, 6(1), 41-48.
2. American Blood Center. (2011). America's blood centers. URL 〈http://www.americasblood.org/〉. Accessed on April 20.
3. Belin, J., & Force, H. (2012). Supply chain management of blood products: A literature review. European Journal of Operational Research, 217(1), 1-16.
4. Blake, J. (2009). On the use of operational research for managing platelet inventory and ordering. Transfusion Editorial, 49(3), 396-401.
5. Blake, J., Thompson, S., Smith, S., Anderson, D., Arellana, R., & Bernard, D. (2003). Optimizing the platelet supply chain in nova scotia. In: 29th Meeting of the European Working Group on Operational Research Applied to Health Services (ORAHS) (Vol. 1(1)). (pp. 511-520). Amsterdam, June 3-7.
6. National Blood Center., 2003. Comprehensive Report on Blood Collection and Transfusion in the United States in 2001. Technical Report, Bethesda Md., USA.
7. Broyles, J., Cochran, J., & Montgomery, M. (2013). A statistical markov chain approximation of transient hospital inpatient inventory. European Journal of Operational Research, 207(1), 1214-1223.
8. Can Blood Serv. Canadian blood services., 2011. Canadian Blood Services. URL 〈http://www.blood.ca〉. Accessed on April 20, 2012.
9. Canadian Blood Services., 2009. Annual Report 2008-2009. Technical Report, Canada. URL 〈http://www.blood.ca/〉.
10. Canadian Blood Services., 2012. Annual Report 2011-2012. Technical Report, Canada. URL 〈http://www.blood.ca/〉.
11. Fontaine, M., Chung, Y., Erhun, F., & Goodnough, L. (2010). Age of blood as a limitation for transfusion: potential impact on blood inventory and availability. Transfusion, 50(10), 2233-2239.
12. George, A., & Powell, B. (2006). Adaptive stepsizes for recursive estimation with applications in approximate dynamic programming. Machine Learning, 65(1), 167-198.
13. George, A., Powell, S., & Kulkarni, W. B. (2008). Value function approximation using multiple aggregation for multiattribute resource management. Journal of Machine Learning Research, 9(1), 2079-2111.
14. Ghandforoush, P., & Sen, T. (2010). A DSS to manage platelet production supply chain for regional blood centers. Decision Support Systems, 50(1), 32-42.
15. Godfrey, G., & Powell, W. B. (2002). An adaptive dynamic programming algorithm for single-period fleet management problems II: Multiperiod travel times. Transportation Science, 56 (1), 40-54.
16. Haijema, R., Van DerWal, J., & Dijk, N. (2007). Blood platelet production: Optimization by dynamic programming and simulation. Computer Operation Research, 34(3), 760-779.
17. Haijema, R., Van DerWal, J., Dijk, N., & Sibinga, C. (2008). Blood platelet production with breaks: Optimization with SDP and simulation. International Journal Production Economy, 49(3), 412-420.
18. Hess, J. R., & Grazzini, G. (2011). Transfusion: Political, administrative and logistic issues, in chemistry and biochemistry of oxygen therapeutics: From transfusion to artificial blood. Chichester, UK: John Wiley and Sons, Ltd. URL http://onlinelibrary.wiley.com/doi/10.1002/9781119975427.ch13/summary. accessed on January 12, 2009.
19. Katz, A., Carter, C., Saxton, P., Blutt, J., & Kakaiya, R. (1983). Simulation analysis of platelet production and inventory management. Vox Sang, 44(1), 31-36.
20. Kopach, R. (2004). Finding the optimal switchover level between two levels of demand in a blood bank, University of Toronto AAT MQ 95492, Toronto, Canada.
21. Ma, J., & Powell, W. (2008). Convergence proofs of least squares policy iteration algorithm for high-dimensional infinite horizon markov decision process problems (pp. 1-49)
22. Murphy, S. (2005). Platelets from pooled buffy coats: An update. Transfusion, 44(4), 634-639.
23. Nascimento, J., & Powell, W. (2008). Optimal approximate dynamic programming algorithms for a general class of storage problems (pp. 1-40).
24. Nascimento, J., & Powell, W. (2009). An optimal approximate dynamic programming algorithm for the lagged asset acquisition problem. Mathematics of Operations Research, 34(1), 210-237.
25. Neurath, D., Cober, N., & Giulivi, A. (2012). Transfusion and Apheresis Science, 46(3), 337-340.
26. Nguyen, X., Goebel, M., Schober, M., Klüter, H., & Panzer, S. (2010). The detection of platelet antibodies by simultaneous analysis of specific platelet antibodies and the monoclonal antibody specific immobilization of platelet antigens: An interlaboratory comparison. Transfusion, 50(7), 1429-1434.
27. Powell, W. B. (2007). Approximate dynamic programming, solving the curse of dimensionality. New York: Wiley.
28. Powell, W. B. (2010). Merging ai and or to solve high-dimensional stochastic optimization problems using approximate dynamic programming. INFORMS Journal on Computing, 22, 2-17. Amsterdam, jun 25-27-2008.
29. Powell, W. B. (2011a). Approximate dynamic programming i: Modeling. Encyclopedia of operations research and management science (Vol. 1). John Wiley and Sons.
30. Powell, W. B. (2011b). Approximate dynamic programming ii: Algorithms. Encyclopedia of operations research and management science (Vol. 1). John Wiley and Sons.
31. Powell, W. B. (2011c). A tour through the jungle of approximate dynamic programming. Annals of Operations Research, 1, 1. special issue in honor of Cy Derman, jul 6-2011.
32. Powell, W., & Roy, R. (2005). Approximate dynamic programming for high-dimensional resource allocation problems. Neural Networks, 26, 451-463. USA, July 31-August 3.
33. Prastacos, G. (1979). LIFO distribution system. Journal of the Operational Research Society, 30(1), 539-546.
34. Stanger, S., Wilding, R., Yates, N., & Cotton, S. (2002). Blood inventory management: Hospital best practice. Transfusion Medicine Reviews, 26(2), 153-163.
35. Topaloglu, H., & Powell, W. B. (2005). A distributed decision-making structure for dynamic resource allocation using nonlinear functional approximations. Operation Research, 53(2), 281-297.
36. Topaloglu, H., & Powell, W. B. (2006). Dynamic-programming approximations for stochastic time-staged integer multicommodity-flow problems. INFORMS Journal on Computing, 18(1), 31-42.
37. B. Whitaker., 2012. The 2011 National Blood Collection and Utilization Survey Report. Technical Report, OMB Number 0990-0313 USA, 2012. URL 〈http://www.bloodsurvey.org/〉.
38. Ying, W. (2011). First-time blood donors: Demographic trends. Transfusion, 41(3), 360-364.
39. Zhou, D., Leung, L., & Pierskalla, W. (2011). Inventory management of platelets in hospitals: Optimal inventory policy for perishable products with regular and optional expedited replenishments. Manufacturing and Service Operations Management, 13(4), 420-438.