How to cite this paper
Rabbani, M., Aghabegloo, M & Farrokhi-Asl, H. (2017). Solving a bi-objective mathematical programming model for bloodmobiles location routing problem.International Journal of Industrial Engineering Computations , 8(1), 19-32.
Refrences
Beliën, J., & Forcé, H. (2012). Supply chain management of blood products: A literature review. European Journal of Operational Research, 217(1), 1-16.
Brooks, S. P., & Morgan, B. J. (1995). Optimization using simulated annealing. The Statistician, 44(2), 241-257.
Cumming, P. D., Kendall, K. E., Pegels, C. C., Seagle, J. P., & Shubsda, J. F. (1976). A collections planning model for regional blood suppliers: description and validation. Management Science, 22(9), 962-971.
Dongen, A., Ruiter, R., Abraham, C., & Veldhuizen, I. (2014). Predicting blood donation maintenance: the importance of planning future donations.Transfusion, 54(3pt2), 821-827.
Fontaine, M. J., Chung, Y. T., Rogers, W. M., Sussmann, H. D., Quach, P., Galel, S. A., ... & Erhun, F. (2009). Improving platelet supply chains through collaborations between blood centers and transfusion services. Transfusion,49(10), 2040-2047.
Ghandforoush, P., & Sen, T. K. (2010). A DSS to manage platelet production supply chain for regional blood centers. Decision Support Systems, 50(1), 32-42.
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.
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.
Jiménez, M., Arenas, M., Bilbao, A., & Rodrı, M. V. (2007). Linear programming with fuzzy parameters: an interactive method resolution.European Journal of Operational Research, 177(3), 1599-1609.
Katsaliaki, K. (2008). Cost-effective practices in the blood service sector.Health policy, 86(2), 276-287.
Lenstra, J. K. (1997). Local search in combinatorial optimization. Princeton University Press.
Luhandjula, M. K. (2015). Fuzzy optimization: Milestones and perspectives.Fuzzy Sets and Systems, 274, 4-11.
Madden, E., Murphy, E. L., & Custer, B. (2007). Modeling red cell procurement with both double‐red‐cell and whole‐blood collection and the impact of European travel deferral on units available for transfusion.Transfusion, 47(11), 2025-2037.
Nagurney, A., Masoumi, A. H., & Yu, M. (2012). Supply chain network operations management of a blood banking system with cost and risk minimization. Computational Management Science, 9(2), 205-231.
Osorio, A. F., Brailsford, S. C., & Smith, H. K. (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.
Oswalt, R. M. (1977). A review of blood donor motivation and recruitment.Transfusion, 17(2), 123-135.
Pirlot, M. (1992). General local search heuristics in combinatorial optimization: a tutorial. Belgian Journal of Operations Research, Statistics and Computer Science, 32(1-2), 7-69.
Pishvaee, M. S., & Torabi, S. A. (2010). A possibilistic programming approach for closed-loop supply chain network design under uncertainty.Fuzzy sets and systems, 161(20), 2668-2683.
Rabbani, M., Farrokhi-asl, H., & Rafiei, H. (2016). A hybrid genetic algorithm for waste collection problem by heterogeneous fleet of vehicles with multiple separated compartments. Journal of Intelligent & Fuzzy Systems, 30(3), 1817-1830.
Rezaei-Malek, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Bozorgi-Amiri, A. (2016). An interactive approach for designing a robust disaster relief logistics network with perishable commodities. Computers & Industrial Engineering,94, 201-215.
Şahinyazan, F. G., Kara, B. Y., & Taner, M. R. (2015). Selective vehicle routing for a mobile blood donation system. European Journal of Operational Research, 245(1), 22-34.
Selim, H., & Ozkarahan, I. (2008). A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach. The International Journal of Advanced Manufacturing Technology, 36(3-4), 401-418.
Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159(2), 193-214.
US Department of Health and Human Services. (2011). The 2009 national blood collection and utilization survey report. Washington, DC: US Department of Health and Human Services, Office of the Assistant Secretary for Health, 15.
Van Dijk, N., Haijema, R., Van Der Wal, J., & Sibinga, C. S. (2009). Blood platelet production: a novel approach for practical optimization. Transfusion,49(3), 411-420.
Veldhuizen, I. J. T., Doggen, C. J. M., Atsma, F., & De Kort, W. L. A. M. (2009). Donor profiles: demographic factors and their influence on the donor career. Vox sanguinis, 97(2), 129-138.
Veldhuizen, I., Folléa, G., & Kort, W. (2013). Donor cycle and donor segmentation: new tools for improving blood donor management. Vox sanguinis, 105(1), 28-37.
Wang, R. C., & Liang, T. F. (2005). Applying possibilistic linear programming to aggregate production planning. International Journal of Production Economics, 98(3), 328-341.
Xu, J., & Zhou, X. (2013). Approximation based fuzzy multi-objective models with expected objectives and chance constraints: Application to earth-rock work allocation. Information Sciences, 238, 75-95.
Zahraee, S. M., Rohani, J. M., Firouzi, A., & Shahpanah, A. (2015). Efficiency improvement of blood supply chain system using Taguchi method and dynamic simulation. Procedia Manufacturing, 2, 1-5.
Brooks, S. P., & Morgan, B. J. (1995). Optimization using simulated annealing. The Statistician, 44(2), 241-257.
Cumming, P. D., Kendall, K. E., Pegels, C. C., Seagle, J. P., & Shubsda, J. F. (1976). A collections planning model for regional blood suppliers: description and validation. Management Science, 22(9), 962-971.
Dongen, A., Ruiter, R., Abraham, C., & Veldhuizen, I. (2014). Predicting blood donation maintenance: the importance of planning future donations.Transfusion, 54(3pt2), 821-827.
Fontaine, M. J., Chung, Y. T., Rogers, W. M., Sussmann, H. D., Quach, P., Galel, S. A., ... & Erhun, F. (2009). Improving platelet supply chains through collaborations between blood centers and transfusion services. Transfusion,49(10), 2040-2047.
Ghandforoush, P., & Sen, T. K. (2010). A DSS to manage platelet production supply chain for regional blood centers. Decision Support Systems, 50(1), 32-42.
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.
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.
Jiménez, M., Arenas, M., Bilbao, A., & Rodrı, M. V. (2007). Linear programming with fuzzy parameters: an interactive method resolution.European Journal of Operational Research, 177(3), 1599-1609.
Katsaliaki, K. (2008). Cost-effective practices in the blood service sector.Health policy, 86(2), 276-287.
Lenstra, J. K. (1997). Local search in combinatorial optimization. Princeton University Press.
Luhandjula, M. K. (2015). Fuzzy optimization: Milestones and perspectives.Fuzzy Sets and Systems, 274, 4-11.
Madden, E., Murphy, E. L., & Custer, B. (2007). Modeling red cell procurement with both double‐red‐cell and whole‐blood collection and the impact of European travel deferral on units available for transfusion.Transfusion, 47(11), 2025-2037.
Nagurney, A., Masoumi, A. H., & Yu, M. (2012). Supply chain network operations management of a blood banking system with cost and risk minimization. Computational Management Science, 9(2), 205-231.
Osorio, A. F., Brailsford, S. C., & Smith, H. K. (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.
Oswalt, R. M. (1977). A review of blood donor motivation and recruitment.Transfusion, 17(2), 123-135.
Pirlot, M. (1992). General local search heuristics in combinatorial optimization: a tutorial. Belgian Journal of Operations Research, Statistics and Computer Science, 32(1-2), 7-69.
Pishvaee, M. S., & Torabi, S. A. (2010). A possibilistic programming approach for closed-loop supply chain network design under uncertainty.Fuzzy sets and systems, 161(20), 2668-2683.
Rabbani, M., Farrokhi-asl, H., & Rafiei, H. (2016). A hybrid genetic algorithm for waste collection problem by heterogeneous fleet of vehicles with multiple separated compartments. Journal of Intelligent & Fuzzy Systems, 30(3), 1817-1830.
Rezaei-Malek, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Bozorgi-Amiri, A. (2016). An interactive approach for designing a robust disaster relief logistics network with perishable commodities. Computers & Industrial Engineering,94, 201-215.
Şahinyazan, F. G., Kara, B. Y., & Taner, M. R. (2015). Selective vehicle routing for a mobile blood donation system. European Journal of Operational Research, 245(1), 22-34.
Selim, H., & Ozkarahan, I. (2008). A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach. The International Journal of Advanced Manufacturing Technology, 36(3-4), 401-418.
Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, 159(2), 193-214.
US Department of Health and Human Services. (2011). The 2009 national blood collection and utilization survey report. Washington, DC: US Department of Health and Human Services, Office of the Assistant Secretary for Health, 15.
Van Dijk, N., Haijema, R., Van Der Wal, J., & Sibinga, C. S. (2009). Blood platelet production: a novel approach for practical optimization. Transfusion,49(3), 411-420.
Veldhuizen, I. J. T., Doggen, C. J. M., Atsma, F., & De Kort, W. L. A. M. (2009). Donor profiles: demographic factors and their influence on the donor career. Vox sanguinis, 97(2), 129-138.
Veldhuizen, I., Folléa, G., & Kort, W. (2013). Donor cycle and donor segmentation: new tools for improving blood donor management. Vox sanguinis, 105(1), 28-37.
Wang, R. C., & Liang, T. F. (2005). Applying possibilistic linear programming to aggregate production planning. International Journal of Production Economics, 98(3), 328-341.
Xu, J., & Zhou, X. (2013). Approximation based fuzzy multi-objective models with expected objectives and chance constraints: Application to earth-rock work allocation. Information Sciences, 238, 75-95.
Zahraee, S. M., Rohani, J. M., Firouzi, A., & Shahpanah, A. (2015). Efficiency improvement of blood supply chain system using Taguchi method and dynamic simulation. Procedia Manufacturing, 2, 1-5.