Arvan, M., R. (2015). Tavakkoli-Moghaddam, and M. Abdollahi, Designing a bi-objective and multi-product supply chain network for the supply of blood. Uncertain Supply Chain Management, 3(1), 57-68.
Atashpaz-Gargari, E., & Lucas., C. (2007). Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. in 2007 IEEE congress on evolutionary computation. Ieee.
Bain, B.J., (2014). Blood cells: a practical guide. John Wiley & Sons.
Bertsimas, D., & Sim, M. (2002). Robust discrete optimization and network flows 1 introduction. Operations Research, 71(January), 1-26.
Bozorgi Amiri, A., S. Mansoori, and M.S. Pishvaee, Multi-objective Relief Chain Network Design for Earthquake Response under Uncertainties. Journal of Industrial Management Perspective, 2017. 7(Issue 1, Spring 2017): p. 9-36. (In Persian).
Daneshvar, A., Homayounfar, M., & Farahmandnejad, A. (2020). Developing an Intelligent Multi Criteria Clustering Method Based on PROMETHEE. Journal of Industrial Management Perspective, 9(Issue 4), 41-61. (In Persian)
Derikvand, H., et al., (2020). A robust stochastic bi objective model for blood inventory-distribution management in a blood supply chain. European Journal of Industrial Engineering, 14(3), 369-403. (In Persian)
Dillon, M., Oliveira, F., & Abbasi, B. (2017). A two-stage stochastic programming model for inventory management in the blood supply chain. International Journal of Production Economics, 187, 27-41.
Doodman, M., & Bozorgi Amiri, A. (2020). Integrate Blood Supply Chain Network Design with Considering Lateral Transshipment under Uncertainty. Journal of Industrial Management Perspective, 9(Issue 4), 9-40. (In Persian)
Ema, (2007). Guideline on influenza vaccines prepared from viruses with the potential to cause pandemic and intended for use outside of the core dossier context (EMEA/CHMP/VWP/263499/2006). Guideline, 24.
Eskandari-Khanghahi, M., et al. (2018). Designing and optimizing a sustainable supply chain network for a blood platelet bank under uncertainty. Engineering Applications of Artificial Intelligence, 71, 236-250.
Farrokh, M., A. Azar, and G. Jandaghi, Developing a Robust Fuzzy Programming Approach for Closed Loop Supply Chain Design. Journal of Industrial Management Perspective, 2016. 6(Issue 2, Summer 2016): p. 9-43. (In Persian).
Gholami, H.R., Mehdizadeh, E., & Naderi, B. (2018). Algorithm for Assembly Flowshops. Journal of Industrial Management Perspective, 8(Issue 1), 93-111. (In Persian)
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.
Hamdan, B., & Diabat, A. (2019). A two-stage multi-echelon stochastic blood supply chain problem. Computers & Operations Research, 101, 130-143.
Heidari-Fathian, H. & Pasandideh, S.H.R. (2018). Green-blood supply chain network design: Robust optimization, bounded objective function & Lagrangian relaxation. Computers & Industrial Engineering, 122, 95-105.
Horng, M.-F., T.-K. Dao, & Shieh, C.-S. (2017). A multi-objective optimal vehicle fuel consumption based on whale optimization algorithm, in Advances in Intelligent Information Hiding and Multimedia Signal Processing. Springer, 371-380.
Hosseini-Motlagh, S.-M., M.R.G. Samani, & Cheraghi, S. (2020). Robust and stable flexible blood supply chain network design under motivational initiatives. Socio-Economic Planning Sciences, 70, 100725.
Hosseini-Motlagh, S.-M., M.R.G. Samani, & Homaei, S. (2020). Blood supply chain management: robust optimization, disruption risk, and blood group compatibility (a real-life case). Journal of Ambient Intelligence and Humanized Computing, 11(3), 1085-1104.
Jokar, M., M. Mozafari, and A. Akbari, A Weighted Robust Two-Stage Stochastic Optimization Model for Supplier Selection and Order Allocation under Uncertainty. Journal of Industrial Management Perspective, 2020. 10(Issue 2, Summer 2020): p. 111-135. (In Persian).
Kamyabniya, A., et al., (2018). Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach. Information Systems Frontiers, 20(4), 759-782.
Larimi, N.G. & Yaghoubi, S. (2019). A robust mathematical model for platelet supply chain considering social announcements and blood extraction technologies. Computers & Industrial Engineering, 137, 106014.
Medicines, E.D.f.t.Q.o., (2013). Guide to the preparation, use and quality assurance of blood components, in Recommendation No. R (95) 15.
Mirjalili, S. & Lewis, A. (2016). The whale optimization algorithm. Advances in engineering software, 95, 51-67.
Nagurney, A., A.H. Masoumi, and M. Yu, Supply chain network operations management of a blood banking system with cost and risk minimization. Computational Management Science, 2012. 9(2): p. 205-231.
Nahmias, S. (1982). Perishable inventory theory: A review. Operations research, 30(4), 680-708.
Osorio, A.F., et al., (2016). Simulation-optimization model for production planning in the blood supply chain. Health care management science, 1-17.
Pierskalla, W.P. (2005). Supply chain management of blood banks, in Operations research and health care., Springer. p. 103-145.
Prastacos, G.P. (1984). Blood inventory management: an overview of theory and practice. Management Science, 30(7), 777-800
Ramezanian, R., & Behboodi, Z. (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.
Zahiri, B. & Pishvaee, M.S. (2016). Blood supply chain network design considering blood group compatibility under uncertainty. International Journal of Production Research, 55(7), 2013-2033.
Zahiri, B., et al. (2018). A multi-stage stochastic programming approach for blood supply chain planning. Computers & Industrial Engineering, 122, 1-14.