References
- Koohathongsumrit N, Meethom W. Route selection in multimodal transportation networks: a hybrid multiple criteria decision-making approach. J Ind Prod Eng. 2021;38(7):171–185.
- Yavari M, Ajalli P. Suppliers’ coalition strategy for green-resilient supply chain network design. J Ind Prod Eng. 2021;38(3):197–212.
- Simaan M, Cruz JB Jr. On the Stackelberg strategy in nonzero-sum games. Journal of Optimization Theory and Applications. 1973;11(5):533–555.
- Aviso KB, Tan RR, Culaba AB, et al. Bi-level fuzzy optimization approach for water exchange in eco-industrial parks. Process SafEnviron Prot. 2010;88(1):31–40.
- Gao J, You F. Game theory approach to optimal design of shale gas supply chains with consideration of economics and life cycle greenhouse gas emissions. AIChE J. 2017;63(7):2671–2693. 2017. .
- Zavadskas EK, Antucheviciene J, Turskis Z, et al. Hybrid multiple-criteria decision-making methods: a review of applications in engineering. Sci Iran. 2016;23(1):1–20.
- Das D, Bhattacharya S, Sarkar B. Material selection in product design under risk and uncertainty introducing the conditional logit in the MADM framework. J Ind Prod Eng. 2019;36(7):440–450.
- Saaty TL. How to make a decision: the analytic hierarchy process. Eur J Oper Res. 1990;48(1):9–26.
- Tan RR, Almario EMR, Aviso KB, et al. A methodology for tracing the rank invariance region in multi-criterion selection problems: application to negative emission technologies. Process Integration and Optimization for Sustainability. 2019;3(2):533–536.
- Chiu ASF, Aviso KB, Baquillas J, et al. Can disruptive events trigger transitions towards sustainable consumption? Cleaner and Responsible Consumption. 2020;1(1):100001.
- Cruz JB Jr., Simaan M. Ordinal games and generalized Nash and Stackelberg solutions. Journal of Optimization Theory and Applications. 2000;107(2):205–222.
- Bard JF. Practical bilevel optimization: algorithms and applications. Dordrecht, The Netherlands: Springer; 1998.
- Bard JF. Some properties of the bilevel programming problem. Journal of Optimization Theory and Applications. 1991;68(2):371–378.
- Shi C, Lu J, Zhang G, et al. An extended branch and bound algorithm for linear bilevel programming. Appl Math Comput. 2006;180(2):529–537.
- Sinha S. Fuzzy programming approach to multi-level programming problems. Fuzzy Sets Syst. 2003;136(2):189–202.
- Chalmardi K, Camacho-Vallejo J-F. A bi-level programming model for sustainable supply chain network design that considers incentives for using cleaner technologies. J Clean Prod. 2019;213(10):1035–1050.
- Sinha A, Malo P, Deb K. A review on bilevel optimization: from classical to evolutionary approaches and applications. IEEE Transactions of Evolutionary Computation. 2018;22(2):276–295.
- Clark PA, Westerberg AW. Bilevel programming for steady-state chemical process design-I. Fundamentals and algorithms. Comput Chem Eng. 1990;14(1):87–97.
- Iyer RR, Grossmann IE. Synthesis and operational planning of utility systems for multiperiod operation. Comput Chem Eng. 1998;22(7–8):979–993.
- Ryu J-H, Dua V, Pistikopoulos EN. A bi-level programming framework for enterprise-wide process networks under uncertainty. Comput Chem Eng. 2004;28(6–7):1121–1129.
- Zhang L, Reniers G, Chen B, et al. CCP game: a game theoretical model for improving the scheduling of chemical cluster patrolling. Reliab Eng Syst Saf. 2018;191(11):106186.
- Khademi A, Eksioglu S. Optimal governmental incentives for biomass cofiring to reduce emissions in the short-term. IISE Trans. 2021;53(8):883–896.
- Cobo S, You F, Dominguez-Ramos A, et al. Noncooperative game theory to ensure the marketability of organic fertilizers within a sustainable circular economy. ACS Sustainable Chem Eng. 2020;8(9):3809–3819.
- Wei W, Liang Y, Liu F, et al. Taxing strategies for carbon emissions: a bilevel optimization approach. Energies. 2014;7(4):2228–2245.
- Schrage LE. LINDO Systems, Inc., Optimization modeling with LINGO. CA, USA: Duxbury Press; 1997.
- Moriarty P, Honnery D. The risk of catastrophic climate change: future energy implications. Futures. 2021;128(4):102728.
- Minx JC, Lamb WF, Callaghan MW, et al. Dominguez, negative emissions – part 1: research landscape and synthesis. Environ Res Lett. 2018;13(6):63001.
- Haszeldine RS, Flude S, Johnson G, et al. V Negative emissions technologies and carbon capture and storage to achieve the Paris agreement commitments, philosophical transactions of the royal society A: mathematical Physical, and Engineering Sciences 2018 3762119 20160447
- Smith P, Haszeldine RS, S,M. Smith. Preliminary assessment of the potential for, and limitations to, terrestrial negative emission technologies in the UK. Environmental Science: Processes and Impacts. 2016;18(11):1400–1405.
- Analjem M, Mostafa MM, ElMelegi AR. Mapping the first decade of circular economy research: a bibliometric network analysis. J Ind Prod Eng. 2021;38(1):29–50.
- Wu C-Y, Hu M-C, Ni F-C. Supporting a circular economy: insights from Taiwan’s plastic waste sector and lessons for developing countries. Sustainable Prod Consumption. 2021;26(4):228–238.
- Tseng M-L, Islam MS, Karia N, et al. A literature review on green supply chain management: trends and future challenges. ResouConserv Recycl. 2018;141(2):145–162.
- Pourjavad E, Shahin A. A hybrid model for analyzing the risks of green supply chain in a fuzzy environment. J Ind Prod Eng. 2020;37(8):422–433.
- Ferrari L, Cavaliere A, De Marchi E, et al. Can nudging improve the environmental impact of food supply chain? A systematic review. Trends Food Sci Technol. 2019;91(9):184–192.