References
1. Moňoková, A. and Vilčeková, S. “Sustainable construction-environmental impacts assessment of architectural elements and building Services”, In International Journal of Engineering Research in Africa, 47, pp. 77-83 (2020). https://doi.org/10.4028/www.scientific.net/JERA.47.77
2. Nikkhah, A., Firouzi, S., Dadaei, K., et al. ‘‘Measuring circularity in food supply chain using life cycle assessment; Refining Oil from Olive Kernel’’, Foods, 10(3), 590 (2021). https://doi.org/10.3390/foods10030590
3. Azhiguzhayeva, A., Basshieva, Z., and Malgarayeva, Z. ‘‘Economic efficiency of housing construction. environmental impact’’, Journal of Environmental Management and Tourism, 12(3), pp. 703-717 (2021). https://doi.org/10.14505//jemt.v12.3(51).10
4. Metham, M., Benjaoran, V., and Sedthamanop, A. ‘‘An evaluation of Green Road Incentive Procurement in road construction projects by using the AHP’’, International Journal of Construction Management, 22(3), pp. 501-513 (2019). https://doi.org/10.1080/15623599.2019.1635757
5. Keshavarz-Ghorabaee, M., Amiri, M., Hashemi-Tabatabaei, M., et al. ‘‘A new decision-making approach based on Fermatean fuzzy sets and WASPAS for green construction supplier evaluation’’, Mathematics, 8(12), 2202 (2020). https://doi.org/10.3390/math8122202
6. Shojaei, P. and Bolvardizadeh, A. ‘‘Rough MCDM model for green supplier selection in Iran: a case of university construction project’’, Built Environment Project and Asset Management, 10(3), pp. 437-452 (2020). https://doi.org/10.1108/BEPAM-11-2019-0117
7. Pitchipoo, P., Venkumar, P., and Rajakarunakaran, S. “Development of fuzzy expert system for supplier evaluation and selection”, In Advances in Engineering, Science and Management (ICAESM), pp. 1-6 (2012).
8. Yazdani, M., Chatterjee, P., Pamucar, D., et al. ‘‘A risk-based integrated decision-making model for green supplier selection: A case study of a construction company in Spain’’, Kybernetes, 49(4), pp. 1229-1252 (2019). https://doi.org/10.1108/K-09-2018-0509
9. Ma, W., Lei, W., and Sun, B. ‘‘Three-way group decisions under hesitant fuzzy linguistic environment for green supplier selection’’, Kybernetes, 49(12), pp. 2919–2945 (2020). https://doi.org/10.1108/K-09-2019-0602
10. Lu, J., Ma, J., Zhang, G., et al. ‘‘Theme-based comprehensive evaluation in new product development using fuzzy hierarchical criteria group decision-making method’’, IEEE Transactions on Industrial Electronics, 58(6), pp. 2236-2246 (2011). https://doi.org/10.1109/TIE.2010.2096171
11. Tsai, C.-C. ‘‘A research on selecting criteria for new green product development project: taking Taiwan consumer electronics products as an example’’, Journal of Cleaner Production, 25, pp. 106-115 (2012). https://doi.org/10.1016/j.jclepro.2011.12.002
12. Oh, J., Yang, J., and Lee, S. ‘‘Managing uncertainty to improve decision-making in NPD portfolio management with a fuzzy expert system’’, Expert Systems with Applications, 39(10), pp. 9868-9885 (2012). https://doi.org/10.1016/j.eswa.2012.02.164
13. Cho, J. and Lee, J. ‘‘Development of a new technology product evaluation model for assessing commercialization opportunities using Delphi method and fuzzy AHP approach’’, Expert Systems with Applications, 40(13), pp. 5314-5330 (2013). https://doi.org/10.1016/j.eswa.2013.03.038
14. Driessen, P.H., Hillebrand, B., Kok, R.A., et al. ‘‘Green new product development: the pivotal role of product greenness’’, IEEE Transactions on Engineering Management, 60(2), pp. 315-326 (2013). https://doi.org/10.1109/TEM.2013.2246792
15. Marmier, F., Deniaud, I.F., and Gourc, D. ‘‘Strategic decision-making in NPD projects according to risk: Application to satellites design projects’’, Computers in Industry, 65(8), pp. 1107-1114 (2014). https://doi.org/10.1016/j.compind.2014.06.001
16. Lin, C.-Y., Lee, A.H., and Kang, H.-Y. ‘‘An integrated new product development framework–an application on green and low-carbon products’’, International Journal of Systems Science, 46(4), pp. 733-753 (2015). https://doi.org/10.1080/00207721.2013.798447
17. Büyüközkan, G. and Güleryüz, S. ‘‘A new integrated intuitionistic fuzzy group decision making approach for product development partner selection’’, Computers and Industrial Engineering, 102, pp. 383-395 (2016). https://doi.org/10.1016/j.cie.2016.05.038
18. Akhavan, P., Hosseini, S.M., and Abbasi, M. ‘‘Selecting new product development team members with knowledge sharing approach: A fuzzy bi-objective optimization model’’, Program, 50(2), pp. 195-214 (2016). https://doi.org/10.1108/PROG-04-2015-0033
19. Afrouzy, Z.A., Nasseri, S.H., Mahdavi, I., et al. ‘‘A fuzzy stochastic multi-objective optimization model to configure a supply chain considering new product development’’, Applied Mathematical Modelling, 40(17-18), pp. 7545-7570 (2016). https://doi.org/10.1016/j.apm.2016.03.015
20. Relich, M. and Pawlewski, P. ‘‘A fuzzy weighted average approach for selecting portfolio of new product development projects’’, Neurocomputing, 231, pp. 19-27 (2017). https://doi.org/10.1016/j.neucom.2016.05.104
21. Abu, N.H., Huat, K.K., and Mansor, M. “Implementation of green new product development among SMEs: Barriers and critical success factors”, In MATEC Web of Conferences, 150 (2018). https://doi.org/10.1051/matecconf/201815005038
22. Oliveira, G.A., Tan, K.H., and Guedes, B.T. ‘‘Lean and green approach: An evaluation tool for new product development focused on small and medium enterprises’’, International Journal of Production Economics, 205, pp. 62-73 (2018). https://doi.org/10.1016/j.ijpe.2018.08.026
23. Pun, K.P., Rotanson, J., Chee-wah, C., et al. ‘‘Application of fuzzy integrated FMEA with product lifetime consideration for new product development in flexible electronics industry’’, Journal of Industrial Engineering and Management, 12(1), pp. 176-200 (2019). https://doi.org/10.3926/jiem.2765
24. Chettibi, S. and Chikhi, S. ‘‘Dynamic fuzzy logic and reinforcement learning for adaptive energy efficient routing in mobile ad-hoc networks’’, Applied Soft Computing, 38, pp. 321-328 (2016). https://doi.org/10.1016/j.asoc.2015.09.003
25. Mardani, A., Zavadskas, E.K., Streimikiene, D., et al. ‘‘Using fuzzy multiple criteria decision making approaches for evaluating energy saving technologies and solutions in five star hotels: A new hierarchical framework’’, Energy, 117, pp. 131-148 (2016). https://doi.org/10.1016/j.energy.2016.10.076
26. Mousavi, M., Gitinavard, H., and Mousavi, S. ‘‘A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information’’, Renewable and Sustainable Energy Reviews, 68, pp. 774-787 (2017). https://doi.org/10.1016/j.rser.2016.09.125
27. Büyüközkan, G. and Güleryüz, S. ‘‘Evaluation of renewable energy resources in Turkey using an integrated MCDM approach with linguistic interval fuzzy preference relations’’, Energy, 123, pp. 149-163 (2017). https://doi.org/10.1016/j.energy.2017.01.137
28. Jayaraman, R., Liuzzi, D., Colapinto, C., et al. ‘‘A fuzzy goal programming model to analyze energy, environmental and sustainability goals of the United Arab Emirates’’, Annals of Operations Research, 251(1-2), pp. 255-270 (2017). https://doi.org/10.1007/s10479-015-1825-5n
29. Wang, E., Alp, N., Shi, J., et al. ‘‘Multi-criteria building energy performance benchmarking through variable clustering based compromise TOPSIS with objective entropy weighting’’, Energy, 125, pp. 197-210 (2017). https://doi.org/10.1016/j.energy.2017.02.131
30. Sindhu, S., Nehra, V., and Luthra, S. ‘‘Solar energy deployment for sustainable future of India: Hybrid SWOC-AHP analysis’’, Renewable and Sustainable Energy Reviews, 72, pp. 1138-1151 (2017). https://doi.org/10.1016/j.rser.2016.10.033
31. Xiang, L. ‘‘Energy network dispatch optimization under emergency of local energy shortage with web tool for automatic large group decision-making’’, Energy, 120, pp. 740-750 (2017). https://doi.org/10.1016/j.energy.2016.11.125
32. Gomes, I., Melicio, R., Mendes, V., et al. ‘‘Decision making for sustainable aggregation of clean energy in day-ahead market: Uncertainty and risk’’, Renewable Energy, 133, pp. 692-702 (2018). https://doi.org/10.1016/j.renene.2018.10.054
33. Lu, P., Yang, X., and Wang, Z.-J. ‘‘Fuzzy group consensus decision making and its use in selecting energy-saving and low-carbon technology schemes in star hotels’’, International Journal of Environmental Research and Public Health, 15(9), 2057 (2018). https://doi.org/10.3390/ijerph15092057
34. Kofinas, P., Dounis, A.I., and Vouros, G. ‘‘Fuzzy Q-Learning for multi-agent decentralized energy management in microgrids’’, Applied Energy, 219, pp. 53-67 (2018). https://doi.org/10.1016/j.apenergy.2018.03.017
35. Jeong, J.S. and Ramírez-Gómez, Á. ‘‘Optimizing the location of a biomass plant with a fuzzy-DEcision-MAking Trial and Evaluation Laboratory (F-DEMATEL) and multi-criteria spatial decision assessment for renewable energy management and long-term sustainability’’, Journal of Cleaner Production, 182, pp. 509-520 (2018). https://doi.org/10.1016/j.jclepro.2017.12.072
36. Ren, J. ‘‘Sustainability prioritization of energy storage technologies for promoting the development of renewable energy: A novel intuitionistic fuzzy combinative distance-based assessment approach’’, Renewable Energy, 121, pp. 666-676 (2018). https://doi.org/10.1016/j.renene.2018.01.087
37. Fathipour, F. and Saidi-Mehrabad, M. ‘‘A multi-objective energy planning considering sustainable development by a TOPSIS-based augmented e-constraint’’, Journal of Renewable and Sustainable Energy, 10(3), 034901 (2018). https://doi.org/10.1063/1.5008545
38. Wang, L., Peng, J.-j., and Wang, J.-q. ‘‘A multi-criteria decision-making framework for risk ranking of energy performance contracting project under picture fuzzy environment’’, Journal of Cleaner Production, 191, pp. 105-118 (2018). https://doi.org/10.1016/j.jclepro.2018.04.169
39. Peng, D.-H. and Wang, H. ‘‘Dynamic hesitant fuzzy aggregation operators in multi-period decision making’’, Kybernetes, 43(5), pp. 715-736 (2014). https://doi.org/10.1108/K-11-2013-0236
40. Awasthi, A., Chauhan, S.S., and Goyal, S. ‘‘A fuzzy multicriteria approach for evaluating environmental performance of suppliers’’, International Journal of Production Economics, 126(2), pp. 370-378 (2010). https://doi.org/10.1016/j.ijpe.2010.04.029
41. Grisi, R.M., Guerra, L., and Naviglio, G. “Supplier performance evaluation for green supply chain management”, In Business Performance Measurement and Management, Springer. pp. 149-163 (2010). https://doi.org/10.1007/978-3-642-04800-5_10
42. Kuo, R., Wang, Y., and Tien, F. ‘‘Integration of artificial neural network and MADA methods for green supplier selection’’, Journal of Cleaner Production, 18(12), pp. 1161-1170 (2010). https://doi.org/10.1016/j.jclepro.2010.03.020
43. Cao, H. “The study of the suppliers evaluating and choosing strategies based on the green supply chain management”, In Business Management and Electronic Information (BMEI), pp. 788-791 (2011). https://doi.org/10.1109/ICBMEI.2011.5920377
44. Yeh, W.-C. and Chuang, M.-C. ‘‘Using multi-objective genetic algorithm for partner selection in green supply chain problems’’, Expert Systems with Applications, 38(4), pp. 4244-4253 (2011). https://doi.org/10.1016/j.eswa.2010.09.091
45. Tseng, M.-L. ‘‘Green supply chain management with linguistic preferences and incomplete information’’, Applied Soft Computing, 11(8), pp. 4894-4903 (2011). https://doi.org/10.1016/j.asoc.2011.06.010
46. Büyüközkan, G. and Çifçi, G. ‘‘A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information’’, Computers in Industry, 62(2), pp. 164-174 (2011). https://doi.org/10.1016/j.compind.2010.10.009
47. Büyüközkan, G. and Çifçi, G. ‘‘A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers’’, Expert Systems with Applications, 39(3), pp. 3000-3011 (2012). https://doi.org/10.1016/j.eswa.2011.08.162
48. Govindan, K., Khodaverdi, R. and Jafarian, A. ‘‘A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach’’, Journal of Cleaner Production, 47, pp. 345-354 (2013). https://doi.org/10.1016/j.jclepro.2012.04.014
49. Yue, Z. ‘‘An extended TOPSIS for determining weights of decision makers with interval numbers’’, Knowledge-Based Systems, 24(1), pp. 146-153 (2011). https://doi.org/10.1016/j.knosys.2010.07.014
50. Ervural, B.C., Zaim, S., Demirel, O.F., et al. ‘‘An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning’’, Renewable and Sustainable Energy Reviews, 82(1), pp. 1538-1550 (2017). https://doi.org/10.1016/j.rser.2017.06.095
51. Çolak, M. and Kaya, İ. ‘‘Prioritization of renewable energy alternatives by using an integrated fuzzy MCDM model: A real case application for Turkey’’, Renewable and Sustainable Energy Reviews, 80, pp. 840-853 (2017). https://doi.org/10.1016/j.rser.2017.05.194
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