Free Access
Issue
RAIRO-Oper. Res.
Volume 54, Number 4, July-August 2020
Page(s) 1013 - 1025
DOI https://doi.org/10.1051/ro/2020014
Published online 13 May 2020
  • A. Adewumi, N. Budlender and M. Olusanya, Optimizing the assignment of blood in a blood banking system: some initial results. In: IEEE World Congress on Computational Intelligence, Brisbane, Australia (2012) 10–15. [Google Scholar]
  • D.V. Angelis, N. Ricciardi and G. Storchi, Optimizing blood assignment in a donation-transfusion system. Int. Trans. Oper. Res 8 (2001) 183–192. [Google Scholar]
  • J. Beliën and H. Forcé, Supply chain management of blood products: a literature review. Oper. Res. 217 (2012) 1–16. [Google Scholar]
  • M. Cohen and W. Pierskalla, Management policies for a regional blood bank. Transfusion 15 (1975) 57–67. [Google Scholar]
  • M. Eskandari-Khanghahi, R. Tavakkoli-Moghaddam, A.A. Taleizadeh and S.H. Amin, Designing and optimizing a sustainable supply chain network for a blood platelet bank under uncertainty. Eng. App. Artif. Intell. 71 (2018) 236–250. [CrossRef] [Google Scholar]
  • P. Ghandforoush and T.K. Sen, A DSS to manage platelet production supply chain for regional blood centers. Decis. Support Syst. 50 (2010) 32–42. [Google Scholar]
  • S. Gunpinar and G. Centeno, Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals. Comput. Oper. Res. 54 (2015) 129–141. [Google Scholar]
  • H. Heidari and S. Pasandideh, Modeling and solving a blood supply chain network: an approach for collection of blood. Int. J. Supply Oper. Manage. 4 (2017) 158–166. [Google Scholar]
  • K. Igwe, M. Olusanya and A. Adewumi, On the performance of GRASP and dynamic programming for the blood assignment problem. In: Vol. 22 of Global Humanitarian Technology Conference (2013) 110–122. [Google Scholar]
  • A. Jabbarzadeh, B. Fahimnia and S. Seuring, Dynamic supply chain network design for the supply of blood in disasters: a robust model with real world application. Trans. Res. 70 (2014) 225–244. [Google Scholar]
  • K. Katsaliaki and S.C. Brailsford, Using simulation to improve the blood supply chain. J. Oper. Res. Soc. 58 (2007) 219–227. [Google Scholar]
  • A. Nagurney, A.H. Masoumi and M. Yu, Supply chain network operations management of a blood banking system with cost and risk minimization. Comput. Manage. Sci. 9 (2012) 205–231. [CrossRef] [Google Scholar]
  • M.O. Olusanya and A.O. Adewumi, Using metaheuristic techniques to optimize the blood assignment problem. International Advance Computing Conference (2014) 1331–1336. [Google Scholar]
  • M.O. Olusanya, M.A. Arasomwan and A.O. Adewumi, Particle swarm optimization for optimizing assignment of blood in banking system. Comput. Math. Methods Med. 33 (2014) 173–189. [Google Scholar]
  • C. Sapountzis, Allocating blood to hospitals from a central blood bank. Eur. J. Oper. Res. 16 (1984) 157–162. [Google Scholar]
  • Y. Sha and J. Huang, The multi-period location-allocation problem of engineering emergency blood supply systems. Syst. Eng. Proc. 5 (2012) 21–28. [CrossRef] [Google Scholar]
  • O.S. Silva Filho, M.A. Carvalho, W. Cezarino, R. Silva and G. Salviano, Demand forecasting for blood components distribution of a blood supply chain. In: Vol. 46 of 6th IFAC Conference on Management and Control of Production (2013) 565–571. [Google Scholar]
  • G.A. Tetteh, Optimal allocation of blood products. Ph.D. thesis, Interdisciplinary Program in Transportation Engineering (2008). [Google Scholar]
  • I. Vananya, A. Maryania, B. Amaliahb, F. Rinaldy and F. Muhammad, Blood traceability system for Indonesian blood supply chain. Ind. Eng. Serv. Sci. Proc. Manuf. 4 (2015) 535–542. [Google Scholar]
  • S.M. Zahraee, J.M. Rohani, A. Firouzi and A. Shahpanah, Efficiency improvement of blood supply chain system using Taguchi method and dynamic simulation. In: Vol. 2 of 2nd International Materials, Industrial, and Manufacturing Engineering Conference, Bali Indonesia (2015) 1–5. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.