Abdulwahab, U. & Wahab, M.I.M, (2014). Approximate dynamic programming modeling for a typical blood platelet bank. Computers & Industrial Engineering, 78, 259-270.
Arvan, Meysam; Tavakkoli-Moghaddam, Reza & Abdollahi, Mohammad, (2015). Designing a bi-objective and multi-product supply chain network for the supply of blood. Uncertain Supply Chain Management, 3, 57-68.
Asllani, Arben, Culler, Elizabeth & Ettkin, Lawrence, (2013). A simulationābased apheresis platelet inventory management model. Transfusion, 54(10), 2730-2735.
Beliën, Jeroen & Forcé, Hein, (2012). Supply chain management of blood products: A literature review. European Journal of Operational Research, 217(1), 1-16.
Civelek, Ismail, Karaesmen, Itir & Scheller-Wolf, Alan, (2015). Blood platelet inventory management with protection levels. European Journal of Operational Research, 243(3), 526-838.
Duan, Jingnan, Su, Qiang, Zhu, Yanhong & Lu, Yuanshan, (2018). Study on the Centralization Strategy of the Blood Allocation Among Different Departments within a Hospital. Journal of Systems Science and Systems Engineering, 27, 417-434.
Ensafian, Hamidreza & Yaghoubi, Saeed, (2017). Robust optimization model for integrated procurement, production and distribution in platelet supply chain. Transportation Research Part E: Logistics and Transportation Review, 103, 32-55.
Ensafian, Hamidreza, Yaghoubi, Saeed & Modarres Yazdi, Mohammad, (2017). Raising quality and safety of platelet transfusion services in a patient-based integrated supply chain under uncertainty. Computers & Chemical Engineering, 106, 355-372.
Eskandari-Khanghahi, Marzieh; Tavakkoli-Moghaddam, Reza; Taleizadeh, Ata Allah & Hassanzadeh Amin, Saman, (2018). Designing and optimizing a sustainable supply chain network for a blood platelet bank under uncertainty. Engineering Applications of Artificial Intelligence, 71, 236-250.
Haijema, René, Wal, Jan Van der & Nico M. van Dijk, (2007). Blood platelet production: Optimization by dynamic programming and simulation. Computers & Operations Research, 34(3), 760-779.
Haghjoo, N.;Tavakkoli-Moghaddam, R.;Shahmoradi-Moghadam, H. & Rahimi, Y., (2020). Reliable blood supply chain network design with facility disruption: A real-world application.Engineering Applications of Artificial Intelligence, 90, 1-18.
Hamdan, Bayan & Diabat, Ali, (2019). A two-stage multi-echelon stochastic blood supply chain problem. Computers & Operations Research, 101, 130-143.
Haeri, A.; Hosseini-Motlagh, S.-M.; Ghatreh Samani, M. R. & M. Rezaei, (2020). A mixed resilient-efficient approach toward blood supply chain network design. International Transactions in Operational Research, 27, 1962–2001.
Hosseinifard, Zahra & Abbasi, Babak, (2018). The inventory centralization impacts on sustainability of the blood supply chain. Computers & Operations Research, 89, 206-212.
Max Shen, Zuo-Jun, Coullard, Collette & Daskin, Mark S, (2003). A Joint Location-Inventory Model. Transportation Science, 37(1), 40-55.
Norouzi, N., Tavakkoli-Moghaddam, R., Ghazanfari, M., Alinaghian, M., Salamatbakhsh, A., (2012). A New Multi-Objective Competitive Open Vehicle Routing Problem Solved by Particle Swarm Optimization. Networks and Spatial Economics, 12, 609-633.
Osorio, Andres F., Brailsford, Sally C. & Smith, Honora, (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.
Pirabán, A., Guerrero, W.J. & Labadie, N., (2019). Survey on blood supply chain management: Models and methods. Computers & Operations Research, 112, 1-23.
Qiu, Ruozhen & Wang, Yizhi, (2016). Supply Chain Network Design under Demand Uncertainty and Supply Disruptions: A Distributionally Robust Optimization Approach. Scientific Programming, 2016(2), 1-15.
Rajendran, Suchithra & Ravindran, A. Ravi, 2017. Platelet ordering policies at hospitals using stochastic integer programming model and heuristic approaches to reduce wastage. Computers and Industrial Engineering, 110, 151-164.
Ramezanian, Reza & Behboodi, Zahra, (2017). Blood supply chain network design under uncertainties in supply and demand considering social aspects. Transportation Research Part E: Logistics and Transportation Review, 104, 69-82.
Seirfried, E., Klueter, H., Weidmann, Christian, Staudenmaier, T., Schrezenmeier, Hubert, Henschler, Reinhard, Greinacher, A. & Mueller, Markus M., (2011). How much blood is needed?. Vox Sanguinis, 100(1), 10-21.
Shokouhifar, M.; Sabbaghi, M. & Pilrvari, N., (2021). Inventory management in blood supply chain considering fuzzy supply/demand uncertainties and lateral transshipment. Transfusion and Apheresis Science,103103.
Yousefi Nejad Attari, Mahdi, & Neishabouri Jami, Ensyieh, (2018). Robust stochastic multi-choice goal programming for blood collection and distribution problem with real application. Journal of Intelligent and Fuzzy Systems, 35(23-24), 1-19.
Zahiri, B.; Torabi, S. Ali; Mohammadi, M. & Aghabegloo, M., (2018). A multi-stage stochastic programming approach for blood supply chain planning. Computers and Industrial Engineering, 122, 1-14.