How to cite this paper
Alinaghian, M., Amanipour, H., Nazarpour, Z & Hassanzadeh, A. (2023). A robust solution for optimizing facility location and network design with diverse link capacities.Journal of Project Management, 8(3), 199-212.
Refrences
Aharon, B. T., Boaz, G., & Shimrit, S. (2009). Robust multi-echelon multi-period inventory control. European Journal of Operational Research, 199(3), 922-935.
Baohua, W., & Shiwei, H. E. (2009). Robust optimization model and algorithm for logistics center location and allocation under uncertain environment. Journal of Transportation Systems Engineering and Information Technology, 9(2), 69-74.
Behdani, B. (2013). Handling disruptions in supply chains: An integrated framework and an agent-based model.
Beraldi, P., Bruni, M. E., & Conforti, D. (2004). Designing robust emergency medical service via stochastic programming. European Journal of Operational Research, 158(1), 183-193.
Berman, O., Krass, D., & Menezes, M. B. C. (2010). Location problems with two unreliable facilities on a line allowing correlated failures. Working Paper, Rotman School of Management, University of Toronto, Toronto, Ontario, Canada.
Brahami, M. A., Dahane, M., Souier, M., & Sahnoun, M. H. (2022). Sustainable capacitated facility location/network design problem: a non-dominated sorting genetic algorithm based multiobjective approach. Annals of Operations Research, 311(2), 821-852.
Carello, G., & Lanzarone, E. (2014). A cardinality-constrained robust model for the assignment problem in home care services. European Journal of Operational Research, 236(2), 748-762.
Farooquie, P., Suhail, A., & Faisal, M. N. (2017). A grey-based approach for managing uncertainties and performance in automotive supply chains. International Journal of Industrial and Systems Engineering, 27(1), 73-89.
Govindan, K., & Fattahi, M. (2017). Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain. International journal of production economics, 183, 680-699.
Govindan, K., Fattahi, M., & Keyvanshokooh, E. (2017). Supply chain network design under uncertainty: A comprehensive review and future research directions. European journal of operational research, 263(1), 108-141.
Gülpınar, N., Pachamanova, D., & Çanakoğlu, E. (2013). Robust strategies for facility location under uncertainty. European Journal of Operational Research, 225(1), 21-35.
Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk–Definition, measure and modeling. Omega, 52, 119-132.
Hu, Q. M., & Hu, Z. H. (2015). A stochastic programming model for hub-and-spoke network with uncertain flows. International Journal of Industrial and Systems Engineering, 21(3), 302-319.
Jabbarzadeh, A., Fahimnia, B., & Seuring, S. (2014). Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application. Transportation research part E: logistics and transportation review, 70, 225-244.
Jabbarzadeh, A., Jalali Naini, S. G., Davoudpour, H., & Azad, N. (2012). Designing a supply chain network under the risk of disruptions. Mathematical Problems in Engineering, 2012.
La Londe, B. J. (1997). Supply chain management: myth or reality?. Supply chain management review, 1(1), 6-7.
Lanzarone, E., & Matta, A. (2012). A cost assignment policy for home care patients. Flexible Services and Manufacturing Journal, 24, 465-495.
Lanzarone, E., & Matta, A. (2014). Robust nurse-to-patient assignment in home care services to minimize overtimes under continuity of care. Operations Research for Health Care, 3(2), 48-58.
Li, J., Liu, Y., Zhang, Y., & Hu, Z. (2015). Robust optimization of fourth party logistics network design under disruptions. Discrete Dynamics in Nature and Society, 2015.
Liberatore, F., Scaparra, M. P., & Daskin, M. S. (2012). Hedging against disruptions with ripple effects in location analysis. Omega, 40(1), 21-30.
Matisziw, T. C., Murray, A. T., & Grubesic, T. H. (2010). Strategic network restoration. Networks and Spatial Economics, 10, 345-361.
Moslemipour, G., Lee, T. S., & Loong, Y. T. (2018). Solving stochastic dynamic facility layout problems using proposed hybrid AC-CS-SA meta-heuristic algorithm. International Journal of Industrial and Systems Engineering, 28(1), 1-31.
Mulvey, J. M., Vanderbei, R. J., & Zenios, S. A. (1995). Robust optimization of large-scale systems. Operations research, 43(2), 264-281.
O’Hanley, J. R., & Church, R. L. (2011). Designing robust coverage networks to hedge against worst-case facility losses. European Journal of Operational Research, 209(1), 23-36.
Oliver, R. K., & Webber, M. D. (1982). Supply-chain management: logistics catches up with strategy. Outlook, 5(1), 42-47.
Pan, F., & Nagi, R. (2010). Robust supply chain design under uncertain demand in agile manufacturing. Computers & operations research, 37(4), 668-683.
Peng, P., Snyder, L. V., Lim, A., & Liu, Z. (2011). Reliable logistics networks design with facility disruptions. Transportation Research Part B: Methodological, 45(8), 1190-1211.
Qi, L., Shen, Z. J. M., & Snyder, L. V. (2010). The effect of supply disruptions on supply chain design decisions. Transportation Science, 44(2), 274-289.
Qi, L., & Shen, Z. J. M. (2007). A supply chain design model with unreliable supply. Naval Research Logistics (NRL), 54(8), 829-844.
Rad, M. F., Sajadi, S. M., & Kashan, A. H. (2015). Determination of optimal production rate in stochastic manufacturing systems by simulation optimisation approach. International Journal of Industrial and Systems Engineering, 20(3), 306-322.
Rahmaniani, R., & Ghaderi, A. (2013). A combined facility location and network design problem with multi-type of capacitated links. Applied Mathematical Modelling, 37(9), 6400-6414.
Sadghiani, N. S., Torabi, S. A., & Sahebjamnia, N. (2015). Retail supply chain network design under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 75, 95-114.
Santoso, T., Ahmed, S., Goetschalckx, M., & Shapiro, A. (2005). A stochastic programming approach for supply chain network design under uncertainty. European Journal of Operational Research, 167(1), 96-115.
Sheppard, E. S. (1974). A conceptual framework for dynamic location—allocation analysis. Environment and Planning a, 6(5), 547-564.
Shishebori, D., & Babadi, A. Y. (2015). Robust and reliable medical services network design under uncertain environment and system disruptions. Transportation Research Part E: Logistics and Transportation Review, 77, 268-288.
Shishebori, D., & Jabalameli, M. S. (2013). Improving the efficiency of medical services systems: a new integrated mathematical modeling approach. Mathematical Problems in Engineering, 2013.
Shishebori, D., Jabalameli, M. S., & Jabbarzadeh, A. (2014). Facility location-network design problem: reliability and investment budget constraint. Journal of Urban Planning and Development, 140(3), 04014005.
Shishebori, D., Snyder, L. V., & Jabalameli, M. S. (2014). A reliable budget-constrained FL/ND problem with unreliable facilities. Networks and Spatial Economics, 14, 549-580.
Snyder, L. V., & Ülker, N. (2005, May). A model for locating capacitated, unreliable facilities. In IERC Conference, Atlanta, GA.
Snyder, L. V. (2003). Supply chain robustness and* reliability: Models and algorithms. Northwestern University.
Snyder, L. V., Atan, Z., Peng, P., Rong, Y., Schmitt, A. J., & Sinsoysal, B. (2016). OR/MS models for supply chain disruptions: A review. Iie Transactions, 48(2), 89-109.
Snyder, L. V., & Daskin, M. S. (2005). Reliability models for facility location: the expected failure cost case. Transportation science, 39(3), 400-416.
Snyder, L. V., & Daskin, M. S. (2006). Stochastic p-robust location problems. Iie Transactions, 38(11), 971-985.
Snyder, L. V., & Daskin, M. S. (2007). Models for reliable supply chain network design. Critical infrastructure: reliability and vulnerability, 257-289.
Tang, C. S. (2006). Perspectives in supply chain risk management. International journal of production economics, 103(2), 451-488.
Tsiakis, P., Shah, N., & Pantelides, C. C. (2001). Design of multi-echelon supply chain networks under demand uncertainty. Industrial & engineering chemistry research, 40(16), 3585-3604.
Yu, C. S., & Li, H. L. (2000). A robust optimization model for stochastic logistic problems. International journal of production economics, 64(1-3), 385-397.
Zare, F., & Lotfi, M. M. (2015). A possibilistic mixed-integer linear programme for dynamic closed-loop supply chain network design under uncertainty. International Journal of Industrial and Systems Engineering, 21(1), 119-140.
Zarindast, A., Hosseini, S. M. S., & Pishvaee, M. S. (2018). A robust possibilistic programming model for simultaneous decision of inventory lot-size, supplier selection and transportation mode selection. International Journal of Industrial and Systems Engineering, 30(3), 346-364.
Baohua, W., & Shiwei, H. E. (2009). Robust optimization model and algorithm for logistics center location and allocation under uncertain environment. Journal of Transportation Systems Engineering and Information Technology, 9(2), 69-74.
Behdani, B. (2013). Handling disruptions in supply chains: An integrated framework and an agent-based model.
Beraldi, P., Bruni, M. E., & Conforti, D. (2004). Designing robust emergency medical service via stochastic programming. European Journal of Operational Research, 158(1), 183-193.
Berman, O., Krass, D., & Menezes, M. B. C. (2010). Location problems with two unreliable facilities on a line allowing correlated failures. Working Paper, Rotman School of Management, University of Toronto, Toronto, Ontario, Canada.
Brahami, M. A., Dahane, M., Souier, M., & Sahnoun, M. H. (2022). Sustainable capacitated facility location/network design problem: a non-dominated sorting genetic algorithm based multiobjective approach. Annals of Operations Research, 311(2), 821-852.
Carello, G., & Lanzarone, E. (2014). A cardinality-constrained robust model for the assignment problem in home care services. European Journal of Operational Research, 236(2), 748-762.
Farooquie, P., Suhail, A., & Faisal, M. N. (2017). A grey-based approach for managing uncertainties and performance in automotive supply chains. International Journal of Industrial and Systems Engineering, 27(1), 73-89.
Govindan, K., & Fattahi, M. (2017). Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain. International journal of production economics, 183, 680-699.
Govindan, K., Fattahi, M., & Keyvanshokooh, E. (2017). Supply chain network design under uncertainty: A comprehensive review and future research directions. European journal of operational research, 263(1), 108-141.
Gülpınar, N., Pachamanova, D., & Çanakoğlu, E. (2013). Robust strategies for facility location under uncertainty. European Journal of Operational Research, 225(1), 21-35.
Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk–Definition, measure and modeling. Omega, 52, 119-132.
Hu, Q. M., & Hu, Z. H. (2015). A stochastic programming model for hub-and-spoke network with uncertain flows. International Journal of Industrial and Systems Engineering, 21(3), 302-319.
Jabbarzadeh, A., Fahimnia, B., & Seuring, S. (2014). Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application. Transportation research part E: logistics and transportation review, 70, 225-244.
Jabbarzadeh, A., Jalali Naini, S. G., Davoudpour, H., & Azad, N. (2012). Designing a supply chain network under the risk of disruptions. Mathematical Problems in Engineering, 2012.
La Londe, B. J. (1997). Supply chain management: myth or reality?. Supply chain management review, 1(1), 6-7.
Lanzarone, E., & Matta, A. (2012). A cost assignment policy for home care patients. Flexible Services and Manufacturing Journal, 24, 465-495.
Lanzarone, E., & Matta, A. (2014). Robust nurse-to-patient assignment in home care services to minimize overtimes under continuity of care. Operations Research for Health Care, 3(2), 48-58.
Li, J., Liu, Y., Zhang, Y., & Hu, Z. (2015). Robust optimization of fourth party logistics network design under disruptions. Discrete Dynamics in Nature and Society, 2015.
Liberatore, F., Scaparra, M. P., & Daskin, M. S. (2012). Hedging against disruptions with ripple effects in location analysis. Omega, 40(1), 21-30.
Matisziw, T. C., Murray, A. T., & Grubesic, T. H. (2010). Strategic network restoration. Networks and Spatial Economics, 10, 345-361.
Moslemipour, G., Lee, T. S., & Loong, Y. T. (2018). Solving stochastic dynamic facility layout problems using proposed hybrid AC-CS-SA meta-heuristic algorithm. International Journal of Industrial and Systems Engineering, 28(1), 1-31.
Mulvey, J. M., Vanderbei, R. J., & Zenios, S. A. (1995). Robust optimization of large-scale systems. Operations research, 43(2), 264-281.
O’Hanley, J. R., & Church, R. L. (2011). Designing robust coverage networks to hedge against worst-case facility losses. European Journal of Operational Research, 209(1), 23-36.
Oliver, R. K., & Webber, M. D. (1982). Supply-chain management: logistics catches up with strategy. Outlook, 5(1), 42-47.
Pan, F., & Nagi, R. (2010). Robust supply chain design under uncertain demand in agile manufacturing. Computers & operations research, 37(4), 668-683.
Peng, P., Snyder, L. V., Lim, A., & Liu, Z. (2011). Reliable logistics networks design with facility disruptions. Transportation Research Part B: Methodological, 45(8), 1190-1211.
Qi, L., Shen, Z. J. M., & Snyder, L. V. (2010). The effect of supply disruptions on supply chain design decisions. Transportation Science, 44(2), 274-289.
Qi, L., & Shen, Z. J. M. (2007). A supply chain design model with unreliable supply. Naval Research Logistics (NRL), 54(8), 829-844.
Rad, M. F., Sajadi, S. M., & Kashan, A. H. (2015). Determination of optimal production rate in stochastic manufacturing systems by simulation optimisation approach. International Journal of Industrial and Systems Engineering, 20(3), 306-322.
Rahmaniani, R., & Ghaderi, A. (2013). A combined facility location and network design problem with multi-type of capacitated links. Applied Mathematical Modelling, 37(9), 6400-6414.
Sadghiani, N. S., Torabi, S. A., & Sahebjamnia, N. (2015). Retail supply chain network design under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 75, 95-114.
Santoso, T., Ahmed, S., Goetschalckx, M., & Shapiro, A. (2005). A stochastic programming approach for supply chain network design under uncertainty. European Journal of Operational Research, 167(1), 96-115.
Sheppard, E. S. (1974). A conceptual framework for dynamic location—allocation analysis. Environment and Planning a, 6(5), 547-564.
Shishebori, D., & Babadi, A. Y. (2015). Robust and reliable medical services network design under uncertain environment and system disruptions. Transportation Research Part E: Logistics and Transportation Review, 77, 268-288.
Shishebori, D., & Jabalameli, M. S. (2013). Improving the efficiency of medical services systems: a new integrated mathematical modeling approach. Mathematical Problems in Engineering, 2013.
Shishebori, D., Jabalameli, M. S., & Jabbarzadeh, A. (2014). Facility location-network design problem: reliability and investment budget constraint. Journal of Urban Planning and Development, 140(3), 04014005.
Shishebori, D., Snyder, L. V., & Jabalameli, M. S. (2014). A reliable budget-constrained FL/ND problem with unreliable facilities. Networks and Spatial Economics, 14, 549-580.
Snyder, L. V., & Ülker, N. (2005, May). A model for locating capacitated, unreliable facilities. In IERC Conference, Atlanta, GA.
Snyder, L. V. (2003). Supply chain robustness and* reliability: Models and algorithms. Northwestern University.
Snyder, L. V., Atan, Z., Peng, P., Rong, Y., Schmitt, A. J., & Sinsoysal, B. (2016). OR/MS models for supply chain disruptions: A review. Iie Transactions, 48(2), 89-109.
Snyder, L. V., & Daskin, M. S. (2005). Reliability models for facility location: the expected failure cost case. Transportation science, 39(3), 400-416.
Snyder, L. V., & Daskin, M. S. (2006). Stochastic p-robust location problems. Iie Transactions, 38(11), 971-985.
Snyder, L. V., & Daskin, M. S. (2007). Models for reliable supply chain network design. Critical infrastructure: reliability and vulnerability, 257-289.
Tang, C. S. (2006). Perspectives in supply chain risk management. International journal of production economics, 103(2), 451-488.
Tsiakis, P., Shah, N., & Pantelides, C. C. (2001). Design of multi-echelon supply chain networks under demand uncertainty. Industrial & engineering chemistry research, 40(16), 3585-3604.
Yu, C. S., & Li, H. L. (2000). A robust optimization model for stochastic logistic problems. International journal of production economics, 64(1-3), 385-397.
Zare, F., & Lotfi, M. M. (2015). A possibilistic mixed-integer linear programme for dynamic closed-loop supply chain network design under uncertainty. International Journal of Industrial and Systems Engineering, 21(1), 119-140.
Zarindast, A., Hosseini, S. M. S., & Pishvaee, M. S. (2018). A robust possibilistic programming model for simultaneous decision of inventory lot-size, supplier selection and transportation mode selection. International Journal of Industrial and Systems Engineering, 30(3), 346-364.