A self-adaptive evolutionary algorithm for a fuzzy multi-objective hub location problem: An integration of responsiveness and social responsibility

Alumur, 2008, Network hub location problems: the state of the art, Eur. J. Oper. Res., 190, 1, 10.1016/j.ejor.2007.06.008 Alumur, 2012, Hub location under uncertainty, Transp. Res. Part B: Methodol., 46, 529, 10.1016/j.trb.2011.11.006 ISO, 2010. Final Draft International Standard ISO/FDIS 26000:2010(E), Guidance on Social Responsibility. Campbell, 1994, Integer programming formulations of discrete hub location problems, Eur. J. Oper. Res., 72, 387, 10.1016/0377-2217(94)90318-2 Campbell, 2012, Twenty-five years of hub location research, Transp. Sci., 46, 153, 10.1287/trsc.1120.0410 Contreras, 2011, Stochastic uncapacitated hub location, Eur. J. Oper. Res., 212, 518, 10.1016/j.ejor.2011.02.018 Dehghanian, 2009, Designing sustainable recovery network of end-of-life products using genetic algorithm, Resour. Conserv. Recycl., 53, 559, 10.1016/j.resconrec.2009.04.007 Devika, 2014, Designing a sustainable closed-loop supply chain network based on triple bottom line approach: a comparison of metaheuristics hybridization techniques, Eur. J. Oper. Res., 235, 594, 10.1016/j.ejor.2013.12.032 Dubois, 2012 Elhedhli, 2005, Hub-and-spoke network design with congestion, Comput. Oper. Res., 32, 1615, 10.1016/j.cor.2003.11.016 Ernst, 1998, Exact and heuristic algorithms for the uncapacitated multiple allocation p-hub median problem, Eur. J. Oper. Res., 104, 100, 10.1016/S0377-2217(96)00340-2 Farahani, 2013, Hub location problems: a review of models, classification, solution techniques, and applications, Comput. Ind. Eng., 64, 1096, 10.1016/j.cie.2013.01.012 Fattahi, 2015, Investigating replenishment policies for centralised and decentralised supply chains using stochastic programming approach, Int. J. Prod. Res., 53, 41, 10.1080/00207543.2014.922710 Ghodratnama, 2015, Robust and fuzzy goal programming optimization approaches for a novel multi-objective hub location-allocation problem: a supply chain overview, Appl. Soft Comput., 37, 255, 10.1016/j.asoc.2015.07.038 da Graça, 2008, Capacitated single allocation hub location problem—a bi-criteria approach, Comput. Oper. Res., 35, 3671, 10.1016/j.cor.2007.04.005 Gross, 2008 Grove, 1986, Hub networks and simulated schedule delay, Pap. Reg. Sci., 59, 103, 10.1111/j.1435-5597.1986.tb00985.x Initiative, G.R., 2013. b. G4 Sustainability Reporting Guidelines. Amsterdam, The Netherlands: GRI,, ed. Ishfaq, 2011, Hub location–allocation in intermodal logistic networks, Eur. J. Oper. Res., 210, 213, 10.1016/j.ejor.2010.09.017 Keyvanshokooh, 2013, A dynamic pricing approach for returned products in integrated forward/reverse logistics network design, Appl. Math. Model., 37, 10182, 10.1016/j.apm.2013.05.042 Keyvanshokooh, 2016, Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition, Eur. J. Oper. Res., 249, 76, 10.1016/j.ejor.2015.08.028 Marianov, 2003, Location models for airline hubs behaving as M/D/c queues, Comput. Oper. Res., 30, 983, 10.1016/S0305-0548(02)00052-7 Masoumzadeh, 2016, A multi-objective fuzzy goal programming P-hub location and protection model with back-up hubs considering hubs establishment fixed costs, Sci. Iran. Trans. E Ind. Eng., 23, 1941 Mohammadi, 2014, Sustainable hub location under mixed uncertainty, Transp. Res. Part E: Logist. Transp. Rev., 62, 89, 10.1016/j.tre.2013.12.005 Mota, 2015, Towards supply chain sustainability: economic, environmental and social design and planning, J. Clean. Prod., 105, 14, 10.1016/j.jclepro.2014.07.052 Niakan, 2014, A multi-objective optimization model for hub network design under uncertainty: an inexact rough-interval fuzzy approach, Eng. Optim., 1 O'kelly, 1986, The location of interacting hub facilities, Transp. Sci., 20, 92, 10.1287/trsc.20.2.92 Pishvaee, 2012, Robust possibilistic programming for socially responsible supply chain network design: a new approach, Fuzzy Sets Syst., 206, 1, 10.1016/j.fss.2012.04.010 Pishvaee, 2014, An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: a case study of medical needle and syringe supply chain, Transp. Res. Part E: Logist. Transp. Rev., 67, 14, 10.1016/j.tre.2014.04.001 Rabbani, 2016, A robust possibilistic programming approach to multiperiod hospital evacuation planning problem under uncertainty, Int. Trans. Oper. Res., 10.1111/itor.12331 Rahimi, 2015, Multi-objective hub network design under uncertainty considering congestion: an M/M/c/K queue system, Appl. Math. Model., 40, 4179 Rezaei-Malek, 2014, Robust humanitarian relief logistics network planning, Uncertain. Supply Chain Manag., 2, 73, 10.5267/j.uscm.2014.1.002 Rezaei-Malek, 2016, An approximation approach to a trade-off among efficiency, efficacy, and balance for relief pre-positioning in disaster management, Transp. Res. Part E: Logist. Transp. Rev., 93, 485, 10.1016/j.tre.2016.07.003 Rezaei-Malek, 2016, An interactive approach for designing a robust disaster relief logistics network with perishable commodities, Comput. Ind. Eng., 94, 201, 10.1016/j.cie.2016.01.014 Rodriguez, 2007, Hub location under capacity constraints, Transp. Res. Part E: Logist. Transp. Rev., 43, 495, 10.1016/j.tre.2006.01.005 Savino, 2007, Environmental plant optimization in small sized enterprises through an operative framework, Int. J. Oper. Quant. Manag., 13, 95 Savino, 2009, A quality management system based on fuzzy quality pointers in ISO 9000, Int. J. Prod. Dev., 8, 419, 10.1504/IJPD.2009.025255 Savino, 2014, Dynamic workforce allocation in a constrained flow shop with multi-agent system, Comput. Ind., 65, 967, 10.1016/j.compind.2014.02.016 Sim, 2009, The stochastic p-hub center problem with service-level constraints, Comput. Oper. Res., 36, 3166, 10.1016/j.cor.2008.11.020 Skorin-Kapov, 1996, Tight linear programming relaxations of uncapacitated p-hub median problems, Eur. J. Oper. Res., 94, 582, 10.1016/0377-2217(95)00100-X Storn, 1997, Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces, J. Glob. Optim., 11, 341, 10.1023/A:1008202821328 Torabi, 2008, An interactive possibilistic programming approach for multiple objective supply chain master planning, Fuzzy Sets Syst., 159, 193, 10.1016/j.fss.2007.08.010 Van Woensel, 2009, A stochastic approach to traffic congestion costs, Comput. Oper. Res., 36, 1731, 10.1016/j.cor.2008.04.008 Van Woensel, 2006, Validating state-dependent queueing models for uninterrupted traffic flows using simulation, 4OR, 4, 159, 10.1007/s10288-005-0085-7 Vidyarthi, N., Tyagi, R.K., Jayaswal, S., 2013. Hub-and-Spoke System Design for Freight Transportation with Priority Consignment Classes. Xu, 2013, Approximation based fuzzy multi-objective models with expected objectives and chance constraints: application to earth-rock work allocation, Inf. Sci., 238, 75, 10.1016/j.ins.2013.02.011 Zhalechian, M., Tavakkoli-Moghaddam, R., Rahimi, Y., 28-30 October 2015. A bi-objective p-hub location problem with a queue system and transportation modes. In: Proceedings of the CIE 45: 2015 International Conference on Computers and Industrial Engineering, Metz, France. Zhalechian, 2016, Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty, Transp. Res. Part E: Logist. Transp. Rev., 89, 182, 10.1016/j.tre.2016.02.011 Zhalechian, 2017, An interactive possibilistic programming approach for a multi-objective hub location problem: economic and environmental design, Appl. Soft Comput., 52, 699, 10.1016/j.asoc.2016.10.002