Sürdürülebilir Tedarikçi Seçimi için Aralık Tip-2 Bulanık Kural Tabanlı BWM Yaklaşımı

Yıl 2022, Cilt: 10 Sayı: 2, 312 - 336, 01.06.2022

Müslüm Öztürk , Belkız Torğul , Turan Paksoy

https://doi.org/10.36306/konjes.991295

Cited By: 1

Öz

Bulanık mantık, insana özgü yaklaşık akıl yürütmeye dayalı bir teoridir ve uygulamaları, klasik yöntemlerin içinden çıkamadığı durumlara daha etkili ve basit çözümler sunabilmektedir. Tip-1 bulanık küme, 0 ile 1 arasında bir üyelik derecesi atanan sürekli (keskin) bir üyelik derecesine sahip olan ve üyelik fonksiyonları ile karakterize edilen bir kümedir. Belirsizliği daha iyi ifade etme gücüne sahip olan Tip-2 bulanık kümeler, o kümedeki her elemana ait üyelik derecelerinin de bir bulanık küme işaret ettiği üyelik fonksiyonları ile belirtilir. Bu sayede Tip-2 bulanık kümeler, bulanık küme teorisine üyelik fonksiyonları belirsizliğini dâhil etmemize izin verir. Uzman bilgisinin kullanılması ve karar verici etkisinin düzeyini yansıtmak için insan duyarlılığının kullanılması bulanık kural tabanlı bir sistem olarak ifade edilmektedir. Son zamanlarda bulanık kuralların çok kriterli karar verme (ÇKKV) yöntemleri ile birlikte sıklıkla kullanıldığı görülmektedir. Yine bulanık kuralların Tip-2 bulanık sayılarla birleştirilmesi de mevcuttur. Bu çalışmada, ÇKKV yöntemlerinden biri olan En İyi En Kötü Yöntemi (BWM), Aralık Tip-2'ye dayalı bulanık kurallarla bütünleştirilmiştir. Geliştirilen hibrit yöntem Aralık Tip-2 Bulanık Kural Tabanlı BWM Yaklaşımı olarak tanımlanmıştır. Önerilen hibrit yöntem, özellikle benzer sıralama konumlarına sahip alternatifler olduğunda bir etki faktörüne sahip olduğundan önemlidir. Nitekim her alternatifte küçük bir fark olsa bile farkı daha iyi (daha hassas) göstererek önerilen yöntemi güçlü ve benzersiz kılmaktadır. Önerilen yaklaşım, BWM ile karşılaştırmalı olarak sürdürülebilir bir tedarikçi seçimi problemine uygulanmıştır. Sonuçlar, IT2 FRB BWM yaklaşımının klasik BWM yöntemine göre alternatifleri sıralamada daha başarılı olduğunu göstermektedir.

Anahtar Kelimeler

BWM, Aralık Tip-2 Bulanık Kümeler, ÇKKV, Kural Tabanlı Sistem, Tedarikçi Seçimi, Sürdürülebilirlik

INTERVAL TYPE-2 FUZZY RULE-BASED BWM APPROACH FOR SUSTAINABLE SUPPLIER SELECTION

Öz

Fuzzy logic is a theory based on human-specific approximate reasoning. Therefore, fuzzy logic applications can bring simple and more effective solutions to situations that classical methods cannot overcome. The type-1 fuzzy set is a set, which has a continuous (crisp) membership degree to which a membership degree between 0 and 1 is assigned, and is characterised by membership functions. Type-2 fuzzy sets, which have the power to express uncertainty better, are expressed by membership functions, where the membership degrees of each element belonging to that set also specify a fuzzy set.Therefore, type-2 fuzzy sets allow us to include the membership functions uncertainty in fuzzy set theory. Using expert knowledge and using sensitivity of human to reflect the level of the decision maker influence is expressed as a fuzzy rule based system. Recently, it has been seen that fuzzy rules are frequently used together with multi-criteria decision making (MCDM) methods. Again, combining fuzzy rules with type-2 fuzzy numbers is also found. In this study, the Best Worst Method (BWM), one of the MCDM methods, has been integrated with fuzzy rules based interval type-2. The developed hybrid method was defined as Interval Type-2 Fuzzy Rule-Based BWM (IT2 FRB BWM). The proposed hybrid method has an important place when there are alternatives with similar ranking positions. Thus, even if there is a small difference in each alternative, it will show the difference better (more sensitively). This makes the proposed hybrid method forceful and unique.The proposed approach has been applied to a sustainable supplier selection problem comparatively with the BWM. The results show that the IT2 FRB BWM approach is more successful in ordering alternatives than the classical BWM method.

Anahtar Kelimeler

BWM, Interval Type-2 Fuzzy Sets, MCDM, Rule-Based System, Supplier Selection, Sustainability

Kaynakça

• Aboutorab, H., Saberi, M., Asadabadi, M.R., Hussain, O., and Chang, E., 2018, "ZBWM: The Z-number extension of Best Worst Method and its application for supplier development", Expert Systems with Applications, 107, 115-125, doi:10.1016/j.eswa.2018.04.015.
• Aijun, L., Ji, X., Lu, H., and Liu, H., 2019, "The selection of 3PRLs on self-service mobile recycling machine: Interval-valued pythagorean hesitant fuzzy best-worst multi-criteria group decision-making", Journal of cleaner production, 230, doi:10.1016/j.jclepro.2019.04.257.
• Alikhani, R., Torabi, S.A., and Altay, N., 2019, "Strategic supplier selection under sustainability and risk criteria", International Journal of Production Economics, 208, 69-82, doi:10.1016/j.ijpe.2018.11.018.
• Amiri, M., Hashemi-Tabatabaei, M., Ghahremanloo, M., Keshavarz-Ghorabaee, M., Zavadskas, E.K. and Banaitis, A., 2021, “A new fuzzy BWM approach for evaluating and selecting a sustainable supplier in supply chain management”, International Journal of Sustainable Development & World Ecology, 28(2), 125-142, doi:10.1080/13504509.2020.1793424.
• Awasthi, A., Chauhan, S., and Omrani, H., 2011, "Application of fuzzy TOPSIS in evaluating sustainable transportation systems", Expert Syst. Appl., 38, 12270-12280, doi:10.1016/j.eswa.2011.04.005.
• Awasthi, A., Govindan, K., and Gold, S., 2018, "Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach", International Journal of Production Economics, 195, 106-117, doi:10.1016/j.ijpe.2017.10.013.
• Azevedo, S.G., Carvalho, H., Ferreira, L.M., and Matias, J.C.O., 2017, "A proposed framework to assess upstream supply chain sustainability", Environment, Development and Sustainability, 19(6), 2253-2273, doi:10.1007/s10668-016-9853-0.
• Bai, C., Kusi-Sarpong, S., Badri Ahmadi, H., and Sarkis, J., 2019, "Social sustainable supplier evaluation and selection: a group decision-support approach", International Journal of Production Research, 57(22), 7046-7067, doi:10.1080/00207543.2019.1574042.
• Bera, A.K., Jana, D.K., Banerjee, D., and Nandy, T., 2021, “A group evaluation method for supplier selection based on interval type-2 fuzzy TOPSIS method”, International Journal of Business Performance and Supply Chain Modelling, 12(1), 1-26.
• Bostancı, B., Yılmaz Bakır, N., Doğan, U., and Koçak Güngör, M., 2017, "Bulanık karar verme teknikleri ile CBS destekli konut memnuniyeti araştırması", Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 32(4), 1193-1208, doi:10.17341/gazimmfd.369540.
• Buckley, J.J., 1985, "Ranking alternatives using fuzzy numbers", Fuzzy Sets and Systems, 15(1), 21-31, doi:https://doi.org/10.1016/0165-0114(85)90013-2.
• Büyüközkan, G., and Çifçi, G., 2012, "A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers", Expert Systems with Applications, 39(3), 3000-3011, doi:10.1016/j.eswa.2011.08.162.
• Carter C.R., and Easton, P.L., 2011, "Sustainable supply chain management: evolution and future directions", International Journal of Physical Distribution & Logistics Management, 41(1), 46-62, doi:10.1108/09600031111101420.
• Celik, E., Yucesan, M. and Gul, M., 2021, “Green supplier selection for textile industry: a case study using BWM-TODIM integration under interval type-2 fuzzy sets”, Environ Sci Pollut Res, 28, 64793–64817, https://doi.org/10.1007/s11356-021-13832-7.
• Chai, J., Liu, J.N.K., and Xu, Z., 2012, "A New Rule-Based SIR Approach To Supplier Selection Under Intuitionistic Fuzzy Environments", International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 20(03), 451-471, doi:10.1142/S0218488512500237.
• Chen, C.T., and Huang, S.F., 2006, "Order-fulfillment ability analysis in the supply-chain system with fuzzy operation times", International Journal of Production Economics, 101(1), 185-193, doi:https://doi.org/10.1016/j.ijpe.2005.05.003.
• Cheraghalipour, A., and Farsad, S., 2018, "A bi-objective sustainable supplier selection and order allocation considering quantity discounts under disruption risks: A case study in plastic industry", Computers & Industrial Engineering, 118, 237-250, doi:https://doi.org/10.1016/j.cie.2018.02.041.
• Demir, L., Akpınar, M.E., Araz, C., and Ilgın, M.A., 2018, "A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT", Expert Systems with Applications, 114, 479-487, doi:https://doi.org/10.1016/j.eswa.2018.07.071.
• Ecer, F., and Pamucar, D., 2020, "Sustainable supplier selection: A novel integrated fuzzy best worst method (F-BWM) and fuzzy CoCoSo with Bonferroni (CoCoSo’B) multi-criteria model", Journal of cleaner production, 266, 121981, doi:https://doi.org/10.1016/j.jclepro.2020.121981.
• Gan, J., Zhong, S., Liu, S., and Yang, D., 2019, "Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment", Discrete Dynamics in Nature and Society, 2019, 1-14, doi:10.1155/2019/2456260.
• Garg, C. P., and Sharma, A., 2020, "Sustainable outsourcing partner selection and evaluation using an integrated BWM–VIKOR framework", Environment, Development and Sustainability, 22(2), 1529-1557, doi:10.1007/s10668-018-0261-5.
• Ghadimi, P., Dargi, A., and Heavey, C., 2017, "Making sustainable sourcing decisions: practical evidence from the automotive industry", International Journal of Logistics Research and Applications, 20(4), 297-321, doi:10.1080/13675567.2016.1227310.
• Ghoushchi, S., Khazaeili, M., Amini, A., and Osgooei, E., 2019, "Multi-criteria sustainable supplier selection using piecewise linear value function and fuzzy best-worst method", Journal of Intelligent & Fuzzy Systems, 37, 1-17, doi:10.3233/JIFS-182609.
• Govindan, K., Jha, P.C., Agarwal, V., and Darbari, J., 2019, "Environmental management partner selection for reverse supply chain collaboration: A sustainable approach", Journal of Environmental Management, 236, 784-797, doi:10.1016/j.jenvman.2018.11.088.
• Govindan, K., Khodaverdi, R., and Jafarian, A., 2013, "A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach", Journal of cleaner production, 47, 345-354, doi:https://doi.org/10.1016/j.jclepro.2012.04.014.
• Guo, C., and Li, X., 2014, "A multi-echelon inventory system with supplier selection and order allocation under stochastic demand", International Journal of Production Economics, 151, doi:10.1016/j.ijpe.2014.01.017.
• Gupta, H., and Barua, M.K., 2017, "Supplier selection among SMEs on the basis of their green innovation ability using BWM and fuzzy TOPSIS", Journal of cleaner production, 152, 242-258, doi:https://doi.org/10.1016/j.jclepro.2017.03.125.
• Haeri, S.A.S., and Rezaei, J., 2019, "A grey-based green supplier selection model for uncertain environments", Journal of cleaner production, 221, doi:10.1016/j.jclepro.2019.02.193.
• Heidarzade, A., Mahdavi, I., and Mahdavi-Amiri, N., 2016, "Supplier selection using a clustering method based on a new distance for interval type-2 fuzzy sets: A case study", Applied Soft Computing, 38, 213-231, doi:https://doi.org/10.1016/j.asoc.2015.09.029.
• Hoseini, S.A., Hashemkhani Zolfani, S., Skačkauskas, P., Fallahpour, A. and Saberi, S., 2022, ”A Combined Interval Type-2 Fuzzy MCDM Framework for the Resilient Supplier Selection Problem”, Mathematics, 10(1), 44, https://www.mdpi.com/2227-7390/10/1/44.
• Ikram, M., Zhang, Q., Sroufe, R., and Ferasso, M., 2020, "The Social Dimensions of Corporate Sustainability: An Integrative Framework Including COVID-19 Insights", Sustainability, 12(20), 8747.
• Javad, M.O.M., Darvishi, M., and Javad, A.O.M., 2020, "Green supplier selection for the steel industry using BWM and fuzzy TOPSIS: A case study of Khouzestan steel company", Sustainable Futures, 2, 100012, doi:https://doi.org/10.1016/j.sftr.2020.100012.
• Kadaifci, C., Asan, U., Serdarasan, S., and Arican, U., 2019, "A new rule-based integrated decision making approach to container transshipment terminal selection", Maritime Policy & Management, 46(2), 237-256, doi:10.1080/03088839.2018.1489149.
• Kahraman, C., Öztayşi, B., Uçal Sarı, İ., and Turanoğlu, E., 2014, "Fuzzy analytic hierarchy process with interval type-2 fuzzy sets", Knowledge-Based Systems, 59, 48-57, doi:https://doi.org/10.1016/j.knosys.2014.02.001.
• Kahraman, C., Ruan, D., and Doǧan, I., 2003, "Fuzzy group decision-making for facility location selection", Information Sciences, 157, 135-153, doi:https://doi.org/10.1016/S0020-0255(03)00183-X.
• Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A., and Diabat, A., 2013, "Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain", Journal of cleaner production, 47, 355-367, doi:https://doi.org/10.1016/j.jclepro.2013.02.010.
• Kannan, D., Mina, H., Nosrati-Abarghooee, S., and Khosrojerdi, G., 2020, "Sustainable circular supplier selection: A novel hybrid approach", Science of The Total Environment, 722, 137936, doi:https://doi.org/10.1016/j.scitotenv.2020.137936.
• Karaöz, A.E., Akyüz, G.A., and Tekin, K. 2019, "Tedarikçi seçimi uygulamalari: bilgi ve iletişim teknolojileri perspektifli bir literatür taraması", Selçuk Üniversitesi Mühendislik, Bilim ve Teknoloji Dergisi, 7(2), 362-378.
• Karnik, N.N., and M. Mendel, J., 2001, "Operations on type-2 fuzzy sets", Fuzzy Sets and Systems, 122(2), 327-348, doi:https://doi.org/10.1016/S0165-0114(00)00079-8.
• Kazemitash, N., Fazlollahtabar, H., and Abbaspour, M., 2021, “Rough Best-Worst Method for Supplier Selection in Biofuel Companies based on Green criteria”, Operational Research in Engineering Sciences: Theory and Applications, 4(2), 1-12. https://doi.org/10.31181/oresta20402001k.
• Keshavarz Ghorabaee, M., Amiri, M., Salehi Sadaghiani, J., and Hassani Goodarzi, G., 2014, "Multiple criteria group decision-making for supplier selection based on COPRAS method with interval type-2 fuzzy sets", The International Journal of Advanced Manufacturing Technology, 75(5-8), 1115-1130, doi:10.1007/s00170-014-6142-7.
• Khoshfetrat, S., Rahiminezhad Galankashi, M., and Almasi, M., 2020, "Sustainable supplier selection and order allocation: a fuzzy approach", Engineering Optimization, 52(9), 1494-1507, doi:10.1080/0305215X.2019.1663185.
• Laosirihongthong, T., Samaranayake, P., and Nagalingam, S., 2019, "A holistic approach to supplier evaluation and order allocation towards sustainable procurement", Benchmarking: An International Journal, 26(8), 2543-2573, doi:10.1108/BIJ-11-2018-0360.
• Li, J., Fang, H., and Song, W., 2019, "Sustainable supplier selection based on SSCM practices: A rough cloud TOPSIS approach", Journal of cleaner production, 222, 606-621, doi:10.1016/j.jclepro.2019.03.070.
• Liu, H.C., Quan, M.Y., Li, Z., and Wang, Z.L., 2019, "A new integrated MCDM model for sustainable supplier selection under interval-valued intuitionistic uncertain linguistic environment", Information Sciences, 486, 254-270, doi:10.1016/j.ins.2019.02.056.
• Liu, P., Gao, H., and Ma, J., 2019, "Novel green supplier selection method by combining quality function deployment with partitioned Bonferroni mean operator in interval type-2 fuzzy environment", Information Sciences, 490, 292-316, doi:10.1016/j.ins.2019.03.079.
• Lo, H.W., Liou, J.J.H., Wang, H.S., and Tsai, Y.S., 2018, "An integrated model for solving problems in green supplier selection and order allocation", Journal of cleaner production, 190, 339-352, doi:https://doi.org/10.1016/j.jclepro.2018.04.105.
• Lu, H., Jiang, S., Song, W., and Ming, X., 2018, "A rough multi-criteria decision-making approach for sustainable supplier selection under vague environment", Sustainability, 10(8), 2622.
• Luthra, S., Govindan, K., Kannan, D., Mangla, S.K., and Garg, C.P., 2017, "An integrated framework for sustainable supplier selection and evaluation in supply chains", Journal of cleaner production, 140, 1686-1698, doi:https://doi.org/10.1016/j.jclepro.2016.09.078.
• Macioł, A., Jędrusik, S., and Rębiasz, B., "Rule-based approach for supplier evaluation", 2013 Federated Conference on Computer Science and Information Systems, 1207-1214, 8-11 Sept. 2013.
• Memari, A., Dargi, A., Akbari Jokar, M.R., Ahmad, R., and Abdul Rahim, A.R., 2019, "Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method", Journal of Manufacturing Systems, 50, 9-24, doi:10.1016/j.jmsy.2018.11.002.
• Mendel, J.M., John, R.I., and Liu, F., 2006, "Interval Type-2 Fuzzy Logic Systems Made Simple", IEEE Transactions on Fuzzy Systems, 14(6), 808-821, doi:10.1109/TFUZZ.2006.879986.
• Mohammed, A., 2019, "Towards a sustainable assessment of suppliers: an integrated fuzzy TOPSIS-possibilistic multi-objective approach", Annals of Operations Research, doi:10.1007/s10479-019-03167-5.
• Mousakhani, S., Nazari-Shirkouhi, S., and Bozorgi-Amiri, A., 2017, "A novel interval type-2 fuzzy evaluation model based group decision analysis for green supplier selection problems: A case study of battery industry", Journal of cleaner production, 168, 205-218, doi:10.1016/j.jclepro.2017.08.154.
• Nourmohamadi Shalke, P., Paydar, M.M., and Hajiaghaei-Keshteli, M., 2018, "Sustainable supplier selection and order allocation through quantity discounts", International Journal of Management Science and Engineering Management, 13(1), 20-32, doi:10.1080/17509653.2016.1269246.
• Özgen, D., Önüt, S., Gülsün, B., Tuzkaya, U.R., and Tuzkaya, G., 2008, "A two-phase possibilistic linear programming methodology for multi-objective supplier evaluation and order allocation problems", Information Sciences, 178(2), 485-500, doi:https://doi.org/10.1016/j.ins.2007.08.002.
• Pamucar, D., Chatterjee, K., and Zavadskas, E.K., 2019, "Assessment of third-party logistics provider using multi-criteria decision-making approach based on interval rough numbers", Computers & Industrial Engineering, 127, 383-407, doi:https://doi.org/10.1016/j.cie.2018.10.023.
• Paul, S.K., 2015, "Supplier selection for managing supply risks in supply chain: a fuzzy approach", The International Journal of Advanced Manufacturing Technology, 79(1), 657-664, doi:10.1007/s00170-015-6867-y.
• Qin, J., and Liu, X. 2019, "Interval Type-2 Fuzzy Group Decision Making by Integrating Improved Best Worst Method with COPRAS for Emergency Material Supplier Selection", Type-2 Fuzzy Decision-Making Theories, Methodologies and Applications, Springer, 249-271.
• Qin, J., Liu, X., and Pedrycz, W., 2017, "An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment", European Journal of operational research, 258(2), 626-638, doi:10.1016/j.ejor.2016.09.059.
• Rafigh, P., Akbari, A., Bidhendi, H. M., and Kashan, A.H., 2021, “A fuzzy rule-based multi-criterion approach for a cooperative green supplier selection problem”, Environ Sci Pollut Res, https://doi.org/10.1007/s11356-021-17015-2.
• Rashidi, K., and Cullinane, K., 2019, "A comparison of fuzzy DEA and fuzzy TOPSIS in sustainable supplier selection: Implications for sourcing strategy", Expert Systems with Applications, 121, 266-281, doi:10.1016/j.eswa.2018.12.025.
• Rezaei, J., 2015, "Best-worst multi-criteria decision-making method", Omega, 53, 49-57, doi:https://doi.org/10.1016/j.omega.2014.11.009.
• Rezaei, J., 2016, "Best-worst multi-criteria decision-making method: Some properties and a linear model", Omega, 64, 126-130, doi:https://doi.org/10.1016/j.omega.2015.12.001.
• Rezaei, J., 2020, “A Concentration Ratio for Non-Linear Best Worst Method”, International Journal of Information Technology & Decision Making, 19(3), pp. 891-907.
• Rezaei, J., Nispeling, T., Sarkis, J., and Tavasszy, L., 2016, "A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method", Journal of cleaner production, 135, 577-588, doi:https://doi.org/10.1016/j.jclepro.2016.06.125.
• Rezaei, J., Wang, J., and Tavasszy, L., 2015, "Linking supplier development to supplier segmentation using Best Worst Method", Expert Systems with Applications, 42(23), 9152-9164, doi:https://doi.org/10.1016/j.eswa.2015.07.073.
• Sanayei, A., Farid Mousavi, S., Abdi, M.R., and Mohaghar, A., 2008, "An integrated group decision-making process for supplier selection and order allocation using multi-attribute utility theory and linear programming", Journal of the Franklin Institute, 345(7), 731-747, doi:https://doi.org/10.1016/j.jfranklin.2008.03.005.
• Schramm, V.B., Cabral, L.P.B., and Schramm, F., 2020, "Approaches for supporting sustainable supplier selection - A literature review", Journal of cleaner production, 273, 123089, doi:https://doi.org/10.1016/j.jclepro.2020.123089.
• Senturk, S., Erginel, N., and Yazırlı, Y., 2017, "Interval Type-2 Fuzzy Analytic Network Process for Modelling a Third-party Logistics (3PL) Company", Journal of Multiple-Valued Logic & Soft Computing, 28.
• Shidpour, H., Shahrokhi, M., and Bernard, A., 2013, "A multi-objective programming approach, integrated into the TOPSIS method, in order to optimize product design; in three-dimensional concurrent engineering", Computers & Industrial Engineering, 64(4), 875-885, doi:https://doi.org/10.1016/j.cie.2012.12.016.
• Simic, V., Gokasar, I., Deveci, M., and Karakurt, A., 2021, “An integrated CRITIC and MABAC based type-2 neutrosophic model for public transportation pricing system selection”, Socio-Economic Planning Sciences: 101157, doi:https://doi.org/10.1016/j.seps.2021.101157.
• Song, W., Xu, Z., and Liu, H.C., 2017, "Developing sustainable supplier selection criteria for solar air-conditioner manufacturer: An integrated approach", Renewable and Sustainable Energy Reviews, 79, 1461-1471, doi:https://doi.org/10.1016/j.rser.2017.05.081.
• Şengül, Ü., Eren, M., Eslamian Shiraz, S., Gezder, V., and Şengül, A.B., 2015, "Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey", Renewable Energy, 75, 617-625, doi:https://doi.org/10.1016/j.renene.2014.10.045.
• Tavana, M., Yazdani, M., and Di Caprio, D., 2017, "An application of an integrated ANP–QFD framework for sustainable supplier selection", International Journal of Logistics Research and Applications, 20(3), 254-275, doi:10.1080/13675567.2016.1219702.
• Tseng, M.L., Lin, Y.-H., Chiu, A., Chia, Y., and Chen, 2008, "Fuzzy AHP-approach to TQM strategy evaluation", IEMS, 7, 34-43.
• Türk, S., John, R., and Özcan, E., "Interval type-2 fuzzy sets in supplier selection", 2014 14th UK Workshop on Computational Intelligence (UKCI) , 1-7, 8-10 Sept. 2014, doi:10.1109/UKCI.2014.6930168.
• Wu, Q., Zhou, L., Chen, Y., and Chen, H., 2019, "An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods", Information Sciences, 502, 394-417, doi:10.1016/j.ins.2019.06.049.
• Xu, Z., Qin, J., Liu, J., and Martínez, L., 2019, "Sustainable supplier selection based on AHPSort II in interval type-2 fuzzy environment", Information Sciences, 483, 273-293, doi:10.1016/j.ins.2019.01.013.
• Yaakob, A.M., Khalif, K.M.N.K., Gegov, A., and Rahman, S. F. A., "Interval type 2- fuzzy rule based system approach for selection of alternatives using TOPSIS", 2015 7th International Joint Conference on Computational Intelligence (IJCCI), Vol. 2, 112-120, 12-14 Nov. 2015.
• Yazdani, M., Chatterjee, P., Zavadskas, E.K., and Hashemkhani Zolfani, S., 2017, "Integrated QFD-MCDM framework for green supplier selection", Journal of cleaner production, 142, 3728-3740, doi:https://doi.org/10.1016/j.jclepro.2016.10.095.
• Yıldızbaşı, A., Öztürk, C., Efendioğlu, D., and Bulkan, S., 2020, "Assessing the social sustainable supply chain indicators using an integrated fuzzy multi-criteria decision-making methods: a case study of Turkey", Environment, Development and Sustainability, doi:10.1007/s10668-020-00774-2.
• Yilmaz, O., Görür, G., and Dereli, T., 2001, Computer Aided Selection of Cutting Parameters by Using Fuzzy Logic.
• Yucesan, M., Mete, S., Serin, F., Celik, E., and Gul, M., 2019, "An Integrated Best-Worst and Interval Type-2 Fuzzy TOPSIS Methodology for Green Supplier Selection", Mathematics, 7(2), doi:10.3390/math7020182.
• Zadeh, L.A., 1965, “Fuzzy sets”, Information and Control, 8(3), 338-353, doi: https://doi.org/10.1016/S0019-9958(65)90241-X.
• Zadeh, L.A., 1975, "The concept of a linguistic variable and its application to approximate reasoning—I", Information Sciences, 8(3), 199-249, doi:https://doi.org/10.1016/0020-0255(75)90036-5.
• Zarbakhshnia, N., and Jaghdani, T.J., 2018, "Sustainable supplier evaluation and selection with a novel two-stage DEA model in the presence of uncontrollable inputs and undesirable outputs: a plastic case study", The International Journal of Advanced Manufacturing Technology, 97(5), 2933-2945, doi:10.1007/s00170-018-2138-z.
• Zhong, L., and Yao, L., 2017, "An ELECTRE I-based multi-criteria group decision making method with interval type-2 fuzzy numbers and its application to supplier selection", Applied Soft Computing, 57, 556-576, doi:10.1016/j.asoc.2017.04.001.