[1] Saghafi, M.M., Optimal pricing to maximize profits and achieve market-share targets for single-product and multiproduct companies, in Issues in Pricing: Theory and Research. 1988, Lexington Books Los Angeles. p. 239-253. [2] Li, J., S. Wang, and T.E. Cheng, Competition and cooperation in a single-retailer two-supplier supply chain with supply disruption. International Journal of Production Economics, 2010. 124(1): p. 137-150. [3] Drezner, Z., Heuristic solution methods for two location problems with unreliable facilities. Journal of the Operational Research Society, 1987. 38(6): p. 509- 514. [4] Fleischmann, M., et al., The impact of product recovery on logistics network design. Production and operations management, 2001. 10(2): p. 156-173. [5] Salema, M.I.G., A.P. Barbosa-Povoa, and A.Q. Novais, An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. European Journal of Operational Research, 2007. 179(3): p. 1063-1077. [6] Church, R. and M.P. Scaparra, Analysis of facility systems’ reliability when subject to attack or a natural disaster, in Critical Infrastructure. 2007, Springer. p. 221-241. [7] Listeş, O. and R. Dekker, A stochastic approach to a case study for product recovery network design. European Journal of Operational Research, 2005. 160(1): p. 268-287. [8] Lu, Z. and N. Bostel, A facility location model for logistics systems including reverse flows: The case of remanufacturing activities. Computers & Operations Research :)2(34 .2007 .p. 299-323. [9] Bollat, R.C.P., Resilient global supply chain network design optimization. 2009, The Pennsylvania State University. [10] Pishvaee, M.S., R.Z. Farahani, and W. Dullaert, A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Computers & operations research, 2010. 37(6): p. 1100-1112. [11] Peng, P., et al., Reliable logistics networks design with facility disruptions. Transportation Research Part B: Methodological, 2011. 45(8): p. 1190-1211. [12] Jabbarzadeh, A., et al., Designing a supply chain network under the risk of disruptions. Mathematical Problems in Engineering, 2012. [13] Azad, N. and H. Davoudpour, Designing a stochastic distribution network model under risk. The International Journal of Advanced Manufacturing Technology, 2013. 64(1-4): p. 23-40. [14] Pishvaee, M.S. and S.A. Torabi, A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy sets and systems, 2010. 161 :)20(p. 2668-2683. [15] Pishvaee, M.S., M. Rabbani, and S.A. Torabi, A robust optimization approach to closed-loop supply chain network design under uncertainty. Applied Mathematical Modelling, 2011. 35(2): p. 637-649. [16] Chen, Q., X. Li, and Y. Ouyang, Joint inventorylocation problem under the risk of probabilistic facility disruptions. Transportation Research Part B: Methodological, 2011. 45(7): p. 991-1003. [17] O’Hanley, J.R., P. Scaparra, and S. García, A General Linearization Technique for Modeling Reliability in Facility Location: Applications to Problems with Site-Dependent Failure Probabilities. 2012. [18] Wang, H., Increasing supply chain robustness through process flexibility and strategic inventory. 2013, Massachusetts Institute of Technology. [19] Ramezani, M., M. Bashiri, and R. TavakkoliMoghaddam, A robust design for a closed-loop supply chain network under an uncertain environment. The International Journal of Advanced Manufacturing Technology, 2013. 66(5-8): p. 825-843. [20] Qiang, Q., et al., The closed-loop supply chain network with competition, distribution channel investment, and uncertainties. Omega, 2013. 41(2): p. 186-194. [21] Amin, S.H. and G. Zhang, A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Applied Mathematical Modelling, 2013. 37(6): p. 4165-4176. [22] Lalmazloumian, M., et al., A robust optimization model for agile and build-to-order supply chain planning under uncertainties. Annals of Operations Research, 2013: p. 1-36. [23] Ramezani, M., et al., Closed-loop supply chain network design under a fuzzy environment. KnowledgeBased Systems, 2014. 59: p. 108-120. [24] Baghalian, A., S. Rezapour, and R.Z. Farahani, Robust supply chain network design with service level against disruptions and demand uncertainties: A reallife case. European Journal of Operational Research, 2013. 227(1): p. 199-215. [25] Özceylan, E., T. Paksoy, and T. Bektaş, Modeling and optimizing the integrated problem of closed-loop supply chain network design and disassembly line balancing. Transportation Research Part E: Logistics and Transportation Review, 2014. 61: p. 142-164. [26] Keyvanshokooh, E., et al., A dynamic pricing approach for returned products in integrated forward/reverse logistics network design. Applied Mathematical Modelling, 2013. 37(24): p. 10182- 10202. [27] Qi, L., Z.-J.M. Shen, and L.V. Snyder, The effect of supply disruptions on supply chain design decisions. Transportation Science, 20 :)2(44 .10p. 274-289. [28] Vahdani, B., et al., Reliable design of a forward/reverse logistics network under uncertainty: a robust-M/M/c queuing model. Transportation Research Part E: Logistics and Transportation Review, 2012. 48(6): p. 1152-1168. [29] Yadegari, E., et al., A Flexible Integrated Forward/Reverse Logistics Model with Random Pathbased Memetic Algorithm. Iranian Journal of Management Studies, 2015. 8(2): p. 287. [30] Aryanezhad, M.-B., S.G. Jalali, and A. Jabbarzadeh, An integrated supply chain design model with random disruptions consideration. African Journal of Business Management, 2010. 4(12): p. 2393. [31] Esmaeilikia, M., et al., A tactical supply chain planning model with multiple flexibility options: an empirical evaluation. Annals of Operations Research, 2014: p. 1-26. [32] Azad, N., et al., Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach. Annals of Operations Research, 2013. 210(1 :) p. 125-163. [33] Demirel, N., et al., A genetic algorithm approach for optimising a closed-loop supply chain network with crisp and fuzzy objectives. International Journal of Production Research, 2014. 52(12): p. 3637-3664. [34] Hatefi, S.M., et al ..A credibility-constrained programming for reliable forward–reverse logistics network design under uncertainty and facility disruptions. International Journal of Computer Integrated Manufacturing, 2015. 28(6): p. 664-678. [35] Hasani, A. and A. Khosrojerdi, Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study. Transportation Research Part E: Logistics and Transportation Review, 2016. 87: p.52-20 . [36] Schmitt, A.J., et al., Centralization versus decentralization: Risk pooling, risk diversification, and supply chain disruptions. Omega, 2015. 52: p. 201-212. [37] Khosrojerdi, A., et al., A method for designing power supply chain networks accounting for failure scenarios and preventive maintenance. Engineering Optimization, 2016. 48(1): p. 154-172.