Sustainable, resilient and responsive mixed supply chain network design under hybrid uncertainty with considering COVID-19 pandemic disruption

Abbas, 2021, Supply chain integrated decision model in order to synergize the energy system of textile industry from its resource waste, Energy, 229, 10.1016/j.energy.2021.120754

Azad, 2013, Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach, Ann. Oper. Res., 210, 125, 10.1007/s10479-012-1146-x

Badri, 2013, Integrated strategic and tactical planning in a supply chain network design with a heuristic solution method, Comput. Oper. Res., 40, 1143, 10.1016/j.cor.2012.11.005

Bairamzadeh, 2018, Modelling different types of uncertainty in biofuel supply network design and planning: a robust optimization approach, Renew. Energy, 116, 500, 10.1016/j.renene.2017.09.020

Bertsimas, 2004, The price of robustness, Oper. Res., 52, 35, 10.1287/opre.1030.0065

Chopra, 2004, Supply-chain breakdown, MIT Sloan Manag. Rev., 46, 53

Darbari, 2017, Fuzzy criteria programming approach for optimising the TBL performance of closed-loop supply chain network design problem, Ann. Oper. Res., 273, 693

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

Dixit, 2016, Performance measures based optimization of supply chain network resilience: a NSGA-II+ Co-Kriging approach, Comput. Ind. Eng., 93, 205, 10.1016/j.cie.2015.12.029

Eskandarpour, 2015, Sustainable supply chain network design: an optimization-oriented review, Omega, 54, 11, 10.1016/j.omega.2015.01.006

Fahimnia, 2016, Marrying supply chain sustainability and resilience: a match made in heaven, Transp. Res. Part E Logist. Transp. Rev., 91, 306, 10.1016/j.tre.2016.02.007

Fahimnia, 2017, Supply chain design for efficient and effective blood supply in disasters, Int. J. Prod. Econ., 183, 700, 10.1016/j.ijpe.2015.11.007

Farrokh, 2018, A novel robust fuzzy stochastic programming for closed-loop supply chain network design under hybrid uncertainty, Fuzzy Sets Syst., 341, 69, 10.1016/j.fss.2017.03.019

Fattahi, 2017, Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers, Transp. Res. Part E Logist. Transp. Rev., 101, 176, 10.1016/j.tre.2017.02.004

Fisher, 2004, The Lagrangian relaxation method for solving integer programming problems, Manag. Sci., 50, 1861, 10.1287/mnsc.1040.0263

Ganguly, 2018, The role of resiliency in managing supply chains disruptions, 237

Goedkoop, M., Heijungs, R., Huijbregts, M., De Schryver, A., Struijs, J.V.Z.R. and Van Zelm, R., 2009. A life cycle impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level. The Hague, Ministry of VROM. ReCiPe.

Ghavamifar, 2018, Designing a resilient competitive supply chain network under disruption risks: a real-world application, Transp. Res. Part E Logist. Transp. Rev., 115, 87, 10.1016/j.tre.2018.04.014

Gholami-Zanjani, 2021, A resilient-green model for multi-echelon meat supply chain planning, Comput. Ind. Eng., 152, 10.1016/j.cie.2020.107018

Gholami-Zanjani, 2021, The design of resilient food supply chain networks prone to epidemic disruptions, Int. J. Prod. Econ., 233, 10.1016/j.ijpe.2020.108001

Gholizadeh, 2020, A robust fuzzy stochastic programming for sustainable procurement and logistics under hybrid uncertainty using big data, J. Clean. Prod., 258, 10.1016/j.jclepro.2020.120640

Govindan, 2017, Fuzzy multi-objective approach for optimal selection of suppliers and transportation decisions in an eco-efficient closed-loop supply chain network, J. Clean. Prod., 165, 1598, 10.1016/j.jclepro.2017.06.180

Govindan, 2017, Supply chain network design under uncertainty: a comprehensive review and future research directions, Eur. J. Oper. Res., 263, 108, 10.1016/j.ejor.2017.04.009

Govindan, 2016, A fuzzy multi-objective optimization model for sustainable reverse logistics network design, Ecol. Indic., 67, 753, 10.1016/j.ecolind.2016.03.017

Govindan, 2019, Designing a sustainable supply chain network integrated with vehicle routing: a comparison of hybrid swarm intelligence metaheuristics, Comput. Oper. Res., 110, 220, 10.1016/j.cor.2018.11.013

Gunasekaran, 2008, Responsive supply chain: a competitive strategy in a networked economy, Omega, 36, 549, 10.1016/j.omega.2006.12.002

Hajiaghaei-Keshteli, 2019, Sustainable closed-loop supply chain network design with discount supposition, Neur. Comput. Appl., 31, 5343, 10.1007/s00521-018-3369-5

Hasani, 2016, Robust global supply chain network design under disruption and uncertainty considering resilience strategies: a parallel memetic algorithm for a real-life case study, Transp. Res. Part E Logist. Transp. Rev., 87, 20, 10.1016/j.tre.2015.12.009

Hasani, 2021, A multi-objective optimization approach for green and resilient supply chain network design: a real-life case study, J. Clean. Prod., 278, 10.1016/j.jclepro.2020.123199

Hosseini-Motlagh, 2020, Innovative strategy to design a mixed resilient-sustainable electricity supply chain network under uncertainty, Appl. Energy, 280, 10.1016/j.apenergy.2020.115921

Ilgin, 2010, Environmentally conscious manufacturing and product recovery (ECMPRO): a review of the state of the art, J. Environ. Manag., 91, 563, 10.1016/j.jenvman.2009.09.037

Ivanov, 2020, Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak, Int. J. Prod. Res., 58, 2904, 10.1080/00207543.2020.1750727

Jabbarzadeh, 2016, Designing a supply chain resilient to major disruptions and supply/demand interruptions, Transp. Res. Part B Methodol., 94, 121, 10.1016/j.trb.2016.09.004

Jabbarzadeh, 2018, Resilient and sustainable supply chain design: sustainability analysis under disruption risks, Int. J. Prod. Res., 56, 5945, 10.1080/00207543.2018.1461950

Jabbarzadeh, 2018, Closed-loop supply chain network design under disruption risks: a robust approach with real world application, Comput. Ind. Eng., 116, 178, 10.1016/j.cie.2017.12.025

Karmaker, 2021, Improving supply chain sustainability in the context of COVID-19 pandemic in an emerging economy: exploring drivers using an integrated model, Sustain. Prod. Consum., 26, 411, 10.1016/j.spc.2020.09.019

Katiyar, 2018, Impact of sustainability and manufacturing practices on supply chain performance: findings from an emerging economy, Int. J. Prod. Econ., 197, 303, 10.1016/j.ijpe.2017.12.007

Mofijur, 2021, Impact of COVID-19 on the social, economic, environmental and energy domains: lessons learnt from a global pandemic, Sustain. Prod. Consum., 26, 343, 10.1016/j.spc.2020.10.016

Mohammed, 2019, A hybrid MCDM-fuzzy multi-objective programming approach for a G-resilient supply chain network design, Comput. Ind. Eng., 127, 297, 10.1016/j.cie.2018.09.052

Mota, 2018, Sustainable supply chains: an integrated modeling approach under uncertainty, Omega, 77, 32, 10.1016/j.omega.2017.05.006

Nagurney, 2010, Optimal supply chain network design and redesign at minimal total cost and with demand satisfaction, Int. J. Prod. Econ., 128, 200, 10.1016/j.ijpe.2010.07.020

Nayeri, 2020, Multi-objective fuzzy robust optimization approach to sustainable closed-loop supply chain network design, Comput. Ind. Eng., 148, 10.1016/j.cie.2020.106716

Nooraie, 2016, Mitigating supply chain disruptions through the assessment of trade-offs among risks, costs and investments in capabilities, Int. J. Prod. Econ., 171, 8, 10.1016/j.ijpe.2015.10.018

Özceylan, 2016, Simultaneous optimization of closed-and open-loop supply chain networks with common components, J. Manuf. Syst., 41, 143, 10.1016/j.jmsy.2016.08.008

Peng, 2011, Reliable logistics networks design with facility disruptions, Transp. Res. Part B Methodol., 45, 1190, 10.1016/j.trb.2011.05.022

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

Ponomarov, 2009, Understanding the concept of supply chain resilience, Int. J. logist. Manag., 10.1108/09574090910954873

Pourmehdi, 2020, Scenario-based design of a steel sustainable closed-loop supply chain network considering production technology, J. Clean. Prod., 277, 10.1016/j.jclepro.2020.123298

Ramezanian, 2019, Green permutation flowshop scheduling problem with sequence-dependent setup times: a case study, Int. J. Prod. Res., 57, 3311, 10.1080/00207543.2019.1581955

Remko, 2020, Research opportunities for a more resilient post-COVID-19 supply chain–closing the gap between research findings and industry practice, Int. J. Oper. Prod. Manag., 40, 341, 10.1108/IJOPM-03-2020-0165

Rezapour, 2017, Resilient supply chain network design under competition: a case study, Eur. J. Oper. Res., 259, 1017, 10.1016/j.ejor.2016.11.041

2008

Rosenthal, 2013

Sabouhi, 2020, A multi-cut l-shaped method for resilient and responsive supply chain network design, Int. J. Prod. Research, 1

Sabouhi, 2021, An optimization approach for sustainable and resilient supply chain design with regional considerations, Comput. Ind. Eng., 159, 10.1016/j.cie.2021.107510

Sabouhi, 2018, Resilient supply chain design under operational and disruption risks considering quantity discount: a case study of pharmaceutical supply chain, Comput. Ind. Eng., 126, 657, 10.1016/j.cie.2018.10.001

Sahebjamnia, 2018, Sustainable tire closed-loop supply chain network design: hybrid metaheuristic algorithms for large-scale networks, J. Clean. Prod., 196, 273, 10.1016/j.jclepro.2018.05.245

Salehi Sadghiani, 2015, Retail supply chain network design under operational and disruption risks, Transp. Res. Part E Logist. Transp. Rev., 75, 95, 10.1016/j.tre.2014.12.015

Salema, 2007, An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty, Eur. J. Oper. Res., 179, 1063, 10.1016/j.ejor.2005.05.032

Sazvar, 2021, A capacity planning approach for sustainable-resilient supply chain network design under uncertainty: a case study of vaccine supply chain, Comput. Ind. Eng., 159, 10.1016/j.cie.2021.107406

Soleimani, 2015, A hybrid particle swarm optimization and genetic algorithm for closed-loop supply chain network design in large-scale networks, Appl. Math. Model., 39, 3990, 10.1016/j.apm.2014.12.016

Soleimani, 2017, Fuzzy multi-objective sustainable and green closed-loop supply chain network design, Comput. Ind. Eng., 109, 191, 10.1016/j.cie.2017.04.038

Taleizadeh, 2019, Modeling and solving a sustainable closed-loop supply chain problem with pricing decisions and discounts on returned products, J. Clean. Prod., 207, 163, 10.1016/j.jclepro.2018.09.198

Van Engeland, 2020, Literature review: strategic network optimization models in waste reverse supply chains, Omega (Westport), 91

Yavari, 2019, An integrated two-layer network model for designing a resilient green-closed loop supply chain of perishable products under disruption, J. Clean. Prod., 230, 198, 10.1016/j.jclepro.2019.04.130

Yu, 2018, Incorporating flexible capacity in the planning of a multi-product multi-echelon sustainable reverse logistics network under uncertainty, J. Clean. Prod., 198, 285, 10.1016/j.jclepro.2018.07.019

Zahiri, 2017, Toward an integrated sustainable-resilient supply chain: a pharmaceutical case study, Transp. Res. Part E Logist. Transp. Rev., 103, 109, 10.1016/j.tre.2017.04.009

Zare Mehrjerdi, 2021, A resilient and sustainable closed-loop supply chain using multiple sourcing and information sharing strategies, J. Clean. Prod., 289

Zhen, 2019, Green and sustainable closed-loop supply chain network design under uncertainty, J. Clean. Prod., 227, 1195, 10.1016/j.jclepro.2019.04.098

Zokaee, 2017, Robust supply chain network design: an optimization model with real world application, Ann. Oper. Res., 257, 15, 10.1007/s10479-014-1756-6