Abdolazimi, O., & Abraham, A. (2020). Designing a multi-objective supply chain model for the oil indus-try in conditions of uncertainty and solving it by meta-heuristic algorithms.
 Abdolazimi, O., Esfandarani, M. S., & Shishebori, D. (2020a). Design of a supply chain network for determining the optimal number of items at the inventory groups based on ABC analysis: a comparison of exact and meta-heuristic methods. Neural Computing and Applications, 1-16.
 Abdolazimi, O., Esfandarani, M. S., Salehi, M., & Shishebori, D. (2020b). Robust design of a multi-objective closed-loop supply chain by integrating on-time delivery, cost, and environmental aspects, case study of a Tire Factory. Journal of Cleaner Production, 121566.
 Abdolazimi, O., Esfandarani, M. S., & Abraham, A. (2020d). Design of a Closed Supply Chain with regards to the Social and Environmental Impacts under Uncertainty.
 Abdolazimi, O., Salehi Esfandarani, M., Salehi, M., & Shishebori, D. (2020c). A Comparison of Solution Methods for the Multi-Objective Closed Loop Supply Chains. Advances in Industrial Engineering, 54(1), 75-98.
 Alfonso, E., Xie, X., Augusto, V., & Garraud, O. (2012). Modeling and simulation of blood collection systems. Health care management science, 15(1), 63-78.
 American Red Cross, (2021). Blood Components. https://www.redcrossblood.org/donate-blood/how-to-donate/types-of-blood-donations/blood-components.html. Accessed February 1, 2021.
 Aouni, B., Colapinto, C., & La Torre, D. (2014). Financial portfolio management through the goal programming model: Current state-of-the-art. European Journal of Operational Research, 234(2), 536-545.
 Bhattacharjee, S., & Ramesh, R. (2000). A multi-period profit maximizing model for retail supply chain management: An integration of demand and supply-side mechanisms. European journal of operational research, 122(3), 584-601.
 Charnes, A., Cooper, W. W., & Ferguson, R. O. (1955). Optimal estimation of executive compensation by linear programming. Management science, 1(2), 138-151.
 Dutta, P., & Nagurney, A. (2019). Multitiered blood supply chain network competition: Linking blood service organizations, hospitals, and payers. Operations Research for Health Care, 23, 100230.
 Fahimnia, B., Jabbarzadeh, A., Ghavamifar, A., & Bell, M. (2017). Supply chain design for efficient and effective blood supply in disasters. International Journal of Production Economics, 183, 700-709.
 Farahani, R. Z., Rezapour, S., Drezner, T., & Fallah, S. (2014). Competitive supply chain network design: An overview of classifications, models, solution techniques and applications. Omega, 45, 92-118.
 Ghare, P. M. (1963). A model for an exponentially decaying inventory. J. ind. Engng, 14, 238-243.
 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, 103493.
 Haijema, R., Van Der Wal, J., & Van Dijk, N. M. (2007). Blood platelet production: Optimization by dynamic programming and simulation. Computers & Operations Research, 34(3), 760-779.
 Hamdan, B., & Diabat, A. (2020). Robust design of blood supply chains under risk of disruptions using Lagrangian relaxation. Transportation Research Part E: Logistics and Transportation Review, 134, 101764.
 Hemmelmayr, V., Doerner, K. F., Hartl, R. F., & Savelsbergh, M. W. (2010). Vendor managed inventory for environments with stochastic product usage. European Journal of Operational Research, 202(3), 686-695.
 Hosseinifard, Z., & Abbasi, B. (2018). The inventory centralization impacts on sustainability of the blood supply chain. Computers & Operations Research, 89, 206-212.
 Hosseini-Motlagh, S. M., Samani, M. R. G., & Cheraghi, S. (2020). Robust and stable flexible blood supply chain network design under motivational initiatives. Socio-Economic Planning Sciences, 70, 100725.
 Hwang, C. L., & Masud, A. S. M. (2012). Multiple objective decision making—methods and applications: a state-of-the-art survey (Vol. 164). Springer Science & Business Media.
 Kaliszewski, I. (1987). A modified weighted Tchebycheff metric for multiple objective programming. Computers & operations research, 14(4), 315-323.
 Karimi-Nasab, M., Shishebori, D., & Jalali-Naini, S. G. R. (2013). Multi-objective optimisation for pricing and distribution in a supply chain with stochastic demands. International Journal of Industrial and Systems Engineering, 13(1), 56-72.
 Khakestari, M., & Abdolazimi, O. (2020). Determine the optimal number of item groups in the werehouse based on ABC analysis within the framework of a supply chain network. Industrial Management Studies, 18(57), 307-344.
 Mavrotas, G. (2009). Effective implementation of the ε-constraint method in multi-objective mathematical programming problems. Applied mathematics and computation, 213(2), 455-465.
 Mavrotas, G., & Florios, K. (2013). An improved version of the augmented ε-constraint method (AUGMECON2) for finding the exact pareto set in multi-objective integer programming problems. Applied Mathematics and Computation, 219(18), 9652-9669.
 Mehrjerdi, Y. Z., & Shafiee, M. (2021). A resilient and sustainable closed-loop supply chain using multiple sourcing and information sharing strategies. Journal of Cleaner Production, 289, 125141.
 Montgomery, D. C. (2017). Design and analysis of experiments. John wiley & sons.
 Nahmias, S. (1982). Perishable inventory theory: A review. Operations research, 30(4), 680-708.
 Niakan, F., & Rahimi, M. (2015). A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach. Transportation Research Part E: Logistics and Transportation Review, 80, 74-94.
 Nurjanni, K. P., & Carvalho, M. S. (2016). Author’ s Accepted Manuscript. Intern. Journal of Production Economics.
 Opricovic, S., & Tzeng, G. H. (2007). Extended VIKOR method in comparison with outranking methods. European journal of operational research, 178(2), 514-529.
 Pirabán, A., Guerrero, W. J., & Labadie, N. (2019). Survey on blood supply chain management: Models and methods. Computers & Operations Research, 112, 104756.
 Puranam, K., Novak, D. C., Lucas, M. T., & Fung, M. (2017). Managing blood inventory with multiple independent sources of supply. European Journal of Operational Research, 259(2), 500-511.
 Sarker, B. R., Jamal, A. M. M., & Wang, S. (2000). Supply chain models for perishable products under inflation and permissible delay in payment. Computers & Operations Research, 27(1), 59-75.
 Shishebori, D., & Jabalameli, M. S. (2013). A new integrated mathematical model for optimizing facility location and network design policies with facility disruptions. Life Sci J, 10(1), 1896-1906.
 Shishebori, D., & Ghaderi, A. (2015). An integrated approach for reliable facility location/network design problem with link disruption. International Journal of Supply and Operations Management, 2(1), 640-661.
 Shishebori, D., Yousefi Babadi, A., & Noormohammadzadeh, Z. (2018). A Lagrangian relaxation approach to fuzzy robust multi-objective facility location network design problem. Scientia Iranica, 25(3), 1750-1767.
 Subulan, K., Taşan, A. S., & Baykasoğlu, A. (2015). A fuzzy goal programming model to strategic planning problem of a lead/acid battery closed-loop supply chain. Journal of Manufacturing Systems, 37, 243-264.
 Teimoury, E., Nedaei, H., Ansari, S., & Sabbaghi, M. (2013). A multi-objective analysis for import quota policy making in a perishable fruit and vegetable supply chain: A system dynamics approach. Computers and electronics in agriculture, 93, 37-45.
 Thangam, A., & Uthayakumar, R. (2009). Two-echelon trade credit financing for perishable items in a supply chain when demand depends on both selling price and credit period. Computers & Industrial Engineering, 57(3), 773-786.
 Van Zyl, G. J. J. (1964). Inventory Control for Perishable Commodities, Unpublished Ph. D. Dissertation, University of North Carolina, Chapel Hill, NC.
 Wang, W., Fung, R. Y., & Chai, Y. (2004). Approach of just-in-time distribution requirements planning for supply chain management. International journal of production economics, 91(2), 101-107.
 Whitin, T. M. (1957). Theory of inventory management. Princeton University Press.
 Zografidou, E., Petridis, K., Petridis, N. E., & Arabatzis, G. (2017). A financial approach to renewable energy production in Greece using goal programming. Renewable energy, 108, 37-51.