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Resilient Supplier Selection Based on Fuzzy AHP-Fuzzy ARAS Methods

Yıl 2022, , 275 - 296, 30.10.2022
https://doi.org/10.17336/igusbd.798775

Öz

Since the success of suppliers affects the success of the entire supply chain, the main source of external risks in supply chains is accepted as suppliers. The ability of suppliers to manage risks and deal with uncertain situations will increase the resilience of the supply chain. In an increasing and varying competitive environment, supplier selection is a complex process that requires decision-makers to consider multiple quantitative and qualitative criteria in order to achieve the best result. The aim of this study is to propose a new multi-criteria decision making (MCDM) approach for resilient supplier selection in the textile industry. In the first stage, the criteria affecting the resilience of the supply chain are defined using expert opinion. As fuzzy set theory helps us better understand and predict uncertainty, the Fuzzy Analytic Hierarchy Process (FAHP) is used to determine the weight of the defined criteria and the Fuzzy Additive Ratio ASsessment (FARAS) to rank suppliers. A real case study is conducted for a company in the textile industry to demonstrate the effectiveness of the proposed MCDM approach. The findings show that the most important factor in the selection of resilient suppliers is resiliency, and the supplier flexibility and responsiveness are found the most important sub-criteria within this factor. The results of this research will assist researchers and decision makers in identifying and applying appropriate methods to identify the most accurate suppliers in the textile industry.

Kaynakça

  • ALAMI MERROUNI, A., ELWALI ELALAOUI, F., MEZRHAB, A., MEZRHAB, A., & GHENNIOUI, A. (2018). Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco. Renewable Energy, 119, 863–873. https://doi.org/10.1016/j.renene.2017.10.044
  • ARABAMERI, A., PRADHAN, B., POURGHASEMI, H. R., & REZAEI, K. (2018). Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS. Geomatics, Natural Hazards and Risk, 9(1), 1129–1155. https://doi.org/10.1080/19475705.2018.1513084
  • ARABAMERI, A., REZAEI, K., CERDÀ, A., CONOSCENTI, C., & KALANTARI, Z. (2019). A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran. Science of the Total Environment, 660, 443–458. https://doi.org/10.1016/j.scitotenv.2019.01.021
  • AWASTHI, A., GOVINDAN, K., & GOLD, S. (2018). Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. International Journal of Production Economics, 195, 106–117. https://doi.org/10.1016/j.ijpe.2017.10.013
  • AZADI, M., JAFARIAN, M., SAEN, R. F., & MIRHEDAYATIAN, S. M. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers and Operations Research, 54, 274–285. https://doi.org/10.1016/j.cor.2014.03.002
  • AZIMIFARD, A., MOOSAVIRAD, S. H., & ARIAFAR, S. (2018). Selecting sustainable supplier countries for Iran’s steel industry at three levels by using AHP and TOPSIS methods. Resources Policy, 57, 30–44. https://doi.org/10.1016/j.resourpol.2018.01.002
  • BALKI, M. K., ERDOĞAN, S., AYDIN, S., & SAYIN, C. (2020). The optimization of engine operating parameters via SWARA and ARAS hybrid method in a small SI engine using alternative fuels. Journal of Cleaner Production, 258, 120685. https://doi.org/10.1016/j.jclepro.2020.120685
  • BANAEIAN, N., MOBLI, H., FAHIMNIA, B., NIELSEN, I. E., & OMID, M. (2018). Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry. Computers & Operations Research, 89, 337–347. https://doi.org/10.1016/J.COR.2016.02.015
  • BRANDON-JONES, E., SQUIRE, B., AUTRY, C. W., & PETERSEN, K. J. (2014). A Contingent Resource-Based Perspective of Supply Chain Resilience and Robustness. Journal of Supply Chain Management, 50(3), 55–73. https://doi.org/10.1111/jscm.12050
  • BUCKLEY, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233–247. https://doi.org/10.1016/0165-0114(85)90090-9
  • BÜYÜKÖZKAN, G., & GÖÇER, F. (2018). An extension of ARAS methodology under Interval Valued Intuitionistic Fuzzy environment for Digital Supply Chain. Applied Soft Computing Journal, 69, 634–654. https://doi.org/10.1016/j.asoc.2018.04.040
  • ÇALIK, A. (2018). Bulanık Çok-Amaçlı Doğrusal Programlama ve Aralık Tip-2 Bulanık AHP Yöntemi ile Yeşil Tedarikçi Seçimi. Içinde Selçuk Ün. Sos. Bil. Ens. Der (C. 0). Tarihinde adresinden erişildi http://dergisosyalbil.selcuk.edu.tr/susbed/article/view/1380
  • ÇALIK, A. (2020). A Comparative Perspective in Sustainable Supplier Selection by Integrated MCDM Techniques. Sigma: Journal of Engineering & Natural Sciences/Mühendislik ve Fen Bilimleri Dergisi, 38(2), 835–852.
  • ÇALIŞ BOYACI, A. (2020). Selection of eco-friendly cities in Turkey via a hybrid hesitant fuzzy decision making approach. Applied Soft Computing Journal, 89, 106090. https://doi.org/10.1016/j.asoc.2020.106090
  • CHRISTOPHER, M., & PECK, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15(2), 1–14. https://doi.org/10.1108/09574090410700275
  • DAVOUDABADI, R., MOUSAVI, S. M., & SHARIFI, E. (2020). An integrated weighting and ranking model based on entropy, DEA and PCA considering two aggregation approaches for resilient supplier selection problem. Journal of Computational Science, 40, 101074. https://doi.org/https://doi.org/10.1016/j.jocs.2019.101074
  • DENIZHAN, B., & YALÇINER, A. Y. (2017). Analitik Hiyerarşi Proses ve Bulanık Analitik Hiyerarşi Proses Yöntemleri Kullanılarak Yeşil Tedarikçi Seçimi Uygulaması. Nevşehir Bilim ve Teknoloji Dergisi, 6(1), 63–78. https://doi.org/10.17100/nevbiltek.288003
  • ECER, F. (2018a). An integrated fuzzy AHP and ARAS model to evaluate mobile banking services. Technological and Economic Development of Economy, 24(2), 670–695. https://doi.org/10.3846/20294913.2016.1255275
  • ECER, F. (2018b). Third-party logistics (3PLs) provider selection via fuzzy AHP and EDAS integrated model. Technological and Economic Development of Economy, 24(2), 615–634. https://doi.org/10.3846/20294913.2016.1213207
  • ERBAŞ, M., KABAK, M., ÖZCEYLAN, E., & ÇETINKAYA, C. (2018). Optimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis. Energy, 163, 1017–1031. https://doi.org/10.1016/j.energy.2018.08.140
  • FATTAHI, R., & KHALILZADEH, M. (2018). Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Safety Science, 102, 290–300. https://doi.org/10.1016/j.ssci.2017.10.018
  • FU, Y. K. (2019). An integrated approach to catering supplier selection using AHP-ARAS-MCGP methodology. Journal of Air Transport Management, 75, 164–169. https://doi.org/10.1016/j.jairtraman.2019.01.011
  • GAN, J., ZHONG, S., LIU, S., & YANG, D. (2019). Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment. Discrete Dynamics in Nature and Society, 2019, 2456260. https://doi.org/10.1155/2019/2456260
  • GHENAI, C., ALBAWAB, M., & BETTAYEB, M. (2020). Sustainability indicators for renewable energy systems using multi-criteria decision-making model and extended SWARA/ARAS hybrid method. Renewable Energy, 146, 580–597. https://doi.org/10.1016/j.renene.2019.06.157
  • GHIMIRE, L. P., & KIM, Y. (2018). An analysis on barriers to renewable energy development in the context of Nepal using AHP. Renewable Energy, 129, 446–456. https://doi.org/10.1016/j.renene.2018.06.011
  • GOVINDAN, K., & SIVAKUMAR, R. (2016). Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches. Annals of Operations Research, 238(1), 243–276. https://doi.org/10.1007/s10479-015-2004-4
  • HALDAR, A., RAY, A., BANERJEE, D., & GHOSH, S. (2012). A hybrid MCDM model for resilient supplier selection. International Journal of Management Science and Engineering Management, 7(4), 284–292. https://doi.org/10.1080/17509653.2012.10671234
  • HOSSEINI, S., & KHALED, A. Al. (2019). A Hybrid Ensemble and AHP Approach for Resilient Supplier Selection. J. Intell. Manuf., 30(1), 207–228. https://doi.org/10.1007/s10845-016-1241-y
  • IGHRAVWE, D. E., & OKE, S. A. (2019). A multi-criteria decision-making framework for selecting a suitable maintenance strategy for public buildings using sustainability criteria. Journal of Building Engineering, 24, 100753. https://doi.org/10.1016/j.jobe.2019.100753
  • ILBAHAR, E., KARAŞAN, A., CEBI, S., & KAHRAMAN, C. (2018). A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Safety Science, 103, 124–136. https://doi.org/10.1016/j.ssci.2017.10.025
  • IVANOV, D. (2018). New Drivers for Supply Chain Structural Dynamics and Resilience: Sustainability, Industry 4.0, Self-Adaptation BT - Structural Dynamics and Resilience in Supply Chain Risk Management. Içinde D. Ivanov (Ed.), Structural Dynamics and Resilience in Supply Chain Risk Management (ss. 293–313). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-69305-7_10
  • JAIN, V., SANGAIAH, A. K., SAKHUJA, S., THODUKA, N., & AGGARWAL, R. (2018). Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry. Neural Computing and Applications, 29(7), 555–564. https://doi.org/10.1007/s00521-016-2533-z
  • KABAK, M., ERBAŞ, M., ÇETINKAYA, C., & ÖZCEYLAN, E. (2018). A GIS-based MCDM approach for the evaluation of bike-share stations. Journal of Cleaner Production, 201, 49–60. https://doi.org/10.1016/j.jclepro.2018.08.033
  • KERŠULIENE, V., & TURSKIS, Z. (2011). Integrated fuzzy multiple criteria decision making model for architect selection. Technological and Economic Development of Economy, 17(4), 645–666. https://doi.org/10.3846/20294913.2011.635718
  • KPMG Türkiye. (2020). Covid-19’un Tedarik Zinciri Üzerindeki Etkilerini Yönetmek Için Olası Stratejik Hamleler. Tarihinde adresinden erişildi https://assets.kpmg/content/dam/kpmg/tr/pdf/2020/03/covid-19-tedarik-zinciri.pdf
  • KRAUSE, D. R., VACHON, S., & ROBERT D., K. (2009). Special Topic Forum on Sustainable Supply Chain Management: Introduction and Reflections on the Role of Purchasing Management. Journal of Supply Chain Management, 45(4), 18–25. https://doi.org/10.1111/j.1745-493X.2009.03173.x
  • KÜÇÜK, O., & ECER, F. (2010). İmalatçı İşletmelerde Uygun Tedarikçi Seçimi: Analitik Hiyerarşi Yöntemi İle Bir Kobi Uygulaması. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 22(2), 435–450.
  • KUO, R. J., WANG, Y. C., & TIEN, F. C. (2010). Integration of artificial neural network and MADA methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161–1170. https://doi.org/10.1016/J.JCLEPRO.2010.03.020
  • LEE, A. H. I. (2009). A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks. Expert Systems with Applications, 36(2), 2879–2893. https://doi.org/10.1016/j.eswa.2008.01.045
  • LIN, H.-F. (2010). An application of fuzzy AHP for evaluating course website quality. Computers & Education, 54(4), 877–888. https://doi.org/10.1016/J.COMPEDU.2009.09.017
  • LUTHRA, S., & MANGLA, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 168–179. https://doi.org/10.1016/j.psep.2018.04.018
  • LYU, H. M., SUN, W. J., SHEN, S. L., & ARULRAJAH, A. (2018). Flood risk assessment in metro systems of mega-cities using a GIS-based modeling approach. Science of the Total Environment, 626, 1012–1025. https://doi.org/10.1016/j.scitotenv.2018.01.138
  • MADENOĞLU, F. S. (2020). Personnel Selection By Using Fuzzy Hybrid Multi Criteria Decision Making Methodology. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 8(3), 953–962. https://doi.org/10.18506/anemon.645838
  • MATIĆ, B., JOVANOVIĆ, S., DAS, D. K., ZAVADSKAS, E. K., STEVIĆ, Ž., SREMAC, S., & MARINKOVIĆ, M. (2019). A New Hybrid MCDM Model: Sustainable Supplier Selection in a Construction Company. Symmetry, 11(3), 353. https://doi.org/10.3390/sym11030353
  • MAVI, R. K. (2015). Green supplier selection: A fuzzy AHP and fuzzy ARAS approach. International Journal of Services and Operations Management, 22(2), 165–188. https://doi.org/10.1504/IJSOM.2015.071528
  • MEDINECKIENE, M., ZAVADSKAS, E. K., BJÖRK, F., & TURSKIS, Z. (2015). Multi-criteria decision-making system for sustainable building assessment/certification. Archives of Civil and Mechanical Engineering, 15(1), 11–18. https://doi.org/10.1016/j.acme.2014.09.001
  • MOHEB-ALIZADEH, H., MAHMOUDI, M., & BAGHERI, R. (2017). Supplier selection and order allocation using a stochastic multi-objective programming model and genetic algorithm. International Journal of Integrated Supply Management, 11(4), 291–315. https://doi.org/10.1504/IJISM.2017.089849
  • MOSTAFAEIPOUR, A., HOSSEINI DEHSHIRI, S. J., & HOSSEINI DEHSHIRI, S. S. (2020). Ranking locations for producing hydrogen using geothermal energy in Afghanistan. International Journal of Hydrogen Energy, 45(32), 15924–15940. https://doi.org/10.1016/j.ijhydene.2020.04.079
  • NAZARI, S., FALLAH, M., KAZEMIPOOR, H., & SALEHIPOUR, A. (2018). A fuzzy inference- fuzzy analytic hierarchy process-based clinical decision support system for diagnosis of heart diseases. Expert Systems with Applications, 95, 261–271. https://doi.org/10.1016/j.eswa.2017.11.001
  • ORUÇ, K. O. (2019). Bulanık Analitik Hiyerarşi Süreci ve Bulanık Aras Yöntemleri Ile Polis Merkezi Kuruluş Yeri Seçimi: Isparta Örneği. Içinde Suleyman Demirel University The Journal of Faculty of Economics and Administrative Sciences Y.2019 (C. 24). Tarihinde adresinden erişildi https://orcid.org/0000-0002-0716-
  • ÖZTÜRK, M., & PAKSOY, T. (2020). Tedarikçi seçimi için yeni bir aralık tip-2 hibrit bulanık kural tabanlı AHP sistemi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 35(3), 1519–1535. https://doi.org/10.17341/gazimmfd.494086
  • PAMUČAR, D., STEVIĆ, Ž., & ZAVADSKAS, E. K. (2018). Integration of interval rough AHP and interval rough MABAC methods for evaluating university web pages. Applied Soft Computing Journal, 67, 141–163. https://doi.org/10.1016/j.asoc.2018.02.057
  • PETROVIĆ, G., MIHAJLOVIĆ, J., ĆOJBAŠIĆ, Ž., MADIĆ, M., & MARINKOVIĆ, D. (2019). Comparison of three fuzzy MCDM methods for solving the supplier selection problem. Facta Universitatis, Series: Mechanical Engineering, 17(3), 455–469. https://doi.org/10.22190/FUME190420039P
  • PRAMANIK, D., HALDAR, A., MONDAL, S. C., NASKAR, S. K., & RAY, A. (2017). Resilient supplier selection using AHP-TOPSIS-QFD under a fuzzy environment. International Journal of Management Science and Engineering Management, 12(1), 45–54. https://doi.org/10.1080/17509653.2015.1101719
  • PwC Türkiye. (2020). COVID-19: Operasyonlar ve Tedarik Zinciri Etkisi. Tarihinde adresinden erişildi https://www.pwc.com.tr/tr/Hizmetlerimiz/danismanlik/tedarik-zinciri-yonetimi/covid-19-operasyonlar-ve-tedarik-zinciri-etkisi.pdf
  • RAJESH, R., & RAVI, V. (2015). Supplier selection in resilient supply chains: a grey relational analysis approach. Journal of Cleaner Production, 86, 343–359. https://doi.org/https://doi.org/10.1016/j.jclepro.2014.08.054
  • REN, C., LI, Z., & ZHANG, H. (2019). Integrated multi-objective stochastic fuzzy programming and AHP method for agricultural water and land optimization allocation under multiple uncertainties. Journal of Cleaner Production, 210, 12–24. https://doi.org/10.1016/j.jclepro.2018.10.348
  • SENNAROGLU, B., & VARLIK CELEBI, G. (2018). A military airport location selection by AHP integrated PROMETHEE and VIKOR methods. Transportation Research Part D: Transport and Environment, 59, 160–173. https://doi.org/10.1016/j.trd.2017.12.022
  • SIRISAWAT, P., & KIATCHAROENPOL, T. (2018). Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers. Computers and Industrial Engineering, 117, 303–318. https://doi.org/10.1016/j.cie.2018.01.015
  • SOLANGI, Y. A., TAN, Q., MIRJAT, N. H., & ALI, S. (2019). Evaluating the strategies for sustainable energy planning in Pakistan: An integrated SWOT-AHP and Fuzzy-TOPSIS approach. Journal of Cleaner Production, 236, 117655. https://doi.org/10.1016/j.jclepro.2019.117655
  • ŠTREIMIKIENE, D., ŠLIOGERIENE, J., & TURSKIS, Z. (2016). Multi-criteria analysis of electricity generation technologies in Lithuania. Renewable Energy, 85, 148–156. https://doi.org/10.1016/j.renene.2015.06.032
  • TIAN, G., ZHANG, H., FENG, Y., WANG, D., PENG, Y., & JIA, H. (2018, Ocak 1). Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method. Renewable and Sustainable Energy Reviews, C. 81, ss. 682–692. Elsevier Ltd. https://doi.org/10.1016/j.rser.2017.08.050
  • TORABI, S. A., BAGHERSAD, M., & MANSOURI, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 79, 22–48. https://doi.org/https://doi.org/10.1016/j.tre.2015.03.005
  • TURSKIS, Z., & ZAVADSKAS, E. K. (2010). A new fuzzy additive ratio assessment method (ARAS‐F). Case study: The analysis of fuzzy multiple criteria in order to select the logistic centers location. Transport, 25(4), 423–432. https://doi.org/10.3846/transport.2010.52
  • VALIPOUR PARKOUHI, S., & SAFAEI GHADIKOLAEI, A. (2017). A resilience approach for supplier selection: Using Fuzzy Analytic Network Process and grey VIKOR techniques. Journal of Cleaner Production, 161, 431–451. https://doi.org/10.1016/J.JCLEPRO.2017.04.175
  • VUGRIN, E. D., WARREN, D. E., & EHLEN, M. A. (2011). A resilience assessment framework for infrastructure and economic systems: Quantitative and qualitative resilience analysis of petrochemical supply chains to a hurricane. Process Safety Progress, 30(3), 280–290. https://doi.org/10.1002/prs.10437
  • WANG, B., SONG, J., REN, J., LI, K., DUAN, H., & WANG, X. (2019). Selecting sustainable energy conversion technologies for agricultural residues: A fuzzy AHP-VIKOR based prioritization from life cycle perspective. Resources, Conservation and Recycling, 142, 78–87. https://doi.org/10.1016/j.resconrec.2018.11.011
  • ZAVADSKAS, E. K., TURSKIS, Z., & VILUTIENE, T. (2010). Multiple criteria analysis of foundation instalment alternatives by applying Additive Ratio Assessment (ARAS) method. Archives of Civil and Mechanical Engineering, 10(3), 123–141. https://doi.org/10.1016/S1644-9665(12)60141-1

Bulanık AHP-Bulanık ARAS Yöntemlerine Dayalı Dayanıklı Tedarikçi Seçimi

Yıl 2022, , 275 - 296, 30.10.2022
https://doi.org/10.17336/igusbd.798775

Öz

Tedarikçilerin başarısı tüm tedarik zincirinin başarısını etkilediğinden tedarik zincirlerinde dış risklerin esas kaynağı tedarikçiler olmaktadır. Tedarikçilerin riskleri yönetme ve belirsiz durumlarla başa çıkma yeteneği, tedarik zincirinin dayanıklılığını artıracaktır. Artan ve farklılaşan bir rekabet ortamında tedarikçi seçimi, karar vericilerin en iyi sonucu elde etmesi için nicel ve nitel çoklu kriterleri dikkate almalarını gerektiren karmaşık bir süreçtir. Bu çalışmanın amacı, tekstil sektöründe dayanıklı tedarikçi seçimi için yeni bir çok kriterli bir karar verme (ÇKKV) yaklaşımı önermektir. İlk aşamada, tedarik zincirinin dayanıklılığını etkileyen kriterler uzman görüşü kullanılarak tanımlanmıştır. Bulanık küme teorisi belirsizliği daha iyi anlamamıza ve daha iyi tahmin etmemize yardımcı olduğu için, tanımlanan kriterlerin ağırlığını belirlemek için Bulanık Analitik Hiyerarşi Süreci (BAHP) ve tedarikçileri sıralamak için Bulanık Additive Ratio ASsessment (BARAS) kullanılmıştır. Önerilen ÇKKV yaklaşımının etkililiğini göstermek için tekstil sektöründeki bir firma için gerçek bir örnek olay uygulaması yapılmıştır. Bulgular, dayanıklı tedarikçi seçiminde en önemli faktörün dayanıklılık olduğunu ve bu faktör içerisinde tedarikçinin esnekliği ve cevap verilebilirlik alt kriterlerinin en önemli olduğunu göstermektedir. Bu araştırmanın sonuçları, tekstil sektöründeki en doğru tedarikçileri belirlemek için uygun yöntemleri belirleme ve uygulama konusunda araştırmacılara ve karar vericilere yardımcı olacaktır.

Kaynakça

  • ALAMI MERROUNI, A., ELWALI ELALAOUI, F., MEZRHAB, A., MEZRHAB, A., & GHENNIOUI, A. (2018). Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco. Renewable Energy, 119, 863–873. https://doi.org/10.1016/j.renene.2017.10.044
  • ARABAMERI, A., PRADHAN, B., POURGHASEMI, H. R., & REZAEI, K. (2018). Identification of erosion-prone areas using different multi-criteria decision-making techniques and GIS. Geomatics, Natural Hazards and Risk, 9(1), 1129–1155. https://doi.org/10.1080/19475705.2018.1513084
  • ARABAMERI, A., REZAEI, K., CERDÀ, A., CONOSCENTI, C., & KALANTARI, Z. (2019). A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran. Science of the Total Environment, 660, 443–458. https://doi.org/10.1016/j.scitotenv.2019.01.021
  • AWASTHI, A., GOVINDAN, K., & GOLD, S. (2018). Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. International Journal of Production Economics, 195, 106–117. https://doi.org/10.1016/j.ijpe.2017.10.013
  • AZADI, M., JAFARIAN, M., SAEN, R. F., & MIRHEDAYATIAN, S. M. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers and Operations Research, 54, 274–285. https://doi.org/10.1016/j.cor.2014.03.002
  • AZIMIFARD, A., MOOSAVIRAD, S. H., & ARIAFAR, S. (2018). Selecting sustainable supplier countries for Iran’s steel industry at three levels by using AHP and TOPSIS methods. Resources Policy, 57, 30–44. https://doi.org/10.1016/j.resourpol.2018.01.002
  • BALKI, M. K., ERDOĞAN, S., AYDIN, S., & SAYIN, C. (2020). The optimization of engine operating parameters via SWARA and ARAS hybrid method in a small SI engine using alternative fuels. Journal of Cleaner Production, 258, 120685. https://doi.org/10.1016/j.jclepro.2020.120685
  • BANAEIAN, N., MOBLI, H., FAHIMNIA, B., NIELSEN, I. E., & OMID, M. (2018). Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry. Computers & Operations Research, 89, 337–347. https://doi.org/10.1016/J.COR.2016.02.015
  • BRANDON-JONES, E., SQUIRE, B., AUTRY, C. W., & PETERSEN, K. J. (2014). A Contingent Resource-Based Perspective of Supply Chain Resilience and Robustness. Journal of Supply Chain Management, 50(3), 55–73. https://doi.org/10.1111/jscm.12050
  • BUCKLEY, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233–247. https://doi.org/10.1016/0165-0114(85)90090-9
  • BÜYÜKÖZKAN, G., & GÖÇER, F. (2018). An extension of ARAS methodology under Interval Valued Intuitionistic Fuzzy environment for Digital Supply Chain. Applied Soft Computing Journal, 69, 634–654. https://doi.org/10.1016/j.asoc.2018.04.040
  • ÇALIK, A. (2018). Bulanık Çok-Amaçlı Doğrusal Programlama ve Aralık Tip-2 Bulanık AHP Yöntemi ile Yeşil Tedarikçi Seçimi. Içinde Selçuk Ün. Sos. Bil. Ens. Der (C. 0). Tarihinde adresinden erişildi http://dergisosyalbil.selcuk.edu.tr/susbed/article/view/1380
  • ÇALIK, A. (2020). A Comparative Perspective in Sustainable Supplier Selection by Integrated MCDM Techniques. Sigma: Journal of Engineering & Natural Sciences/Mühendislik ve Fen Bilimleri Dergisi, 38(2), 835–852.
  • ÇALIŞ BOYACI, A. (2020). Selection of eco-friendly cities in Turkey via a hybrid hesitant fuzzy decision making approach. Applied Soft Computing Journal, 89, 106090. https://doi.org/10.1016/j.asoc.2020.106090
  • CHRISTOPHER, M., & PECK, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15(2), 1–14. https://doi.org/10.1108/09574090410700275
  • DAVOUDABADI, R., MOUSAVI, S. M., & SHARIFI, E. (2020). An integrated weighting and ranking model based on entropy, DEA and PCA considering two aggregation approaches for resilient supplier selection problem. Journal of Computational Science, 40, 101074. https://doi.org/https://doi.org/10.1016/j.jocs.2019.101074
  • DENIZHAN, B., & YALÇINER, A. Y. (2017). Analitik Hiyerarşi Proses ve Bulanık Analitik Hiyerarşi Proses Yöntemleri Kullanılarak Yeşil Tedarikçi Seçimi Uygulaması. Nevşehir Bilim ve Teknoloji Dergisi, 6(1), 63–78. https://doi.org/10.17100/nevbiltek.288003
  • ECER, F. (2018a). An integrated fuzzy AHP and ARAS model to evaluate mobile banking services. Technological and Economic Development of Economy, 24(2), 670–695. https://doi.org/10.3846/20294913.2016.1255275
  • ECER, F. (2018b). Third-party logistics (3PLs) provider selection via fuzzy AHP and EDAS integrated model. Technological and Economic Development of Economy, 24(2), 615–634. https://doi.org/10.3846/20294913.2016.1213207
  • ERBAŞ, M., KABAK, M., ÖZCEYLAN, E., & ÇETINKAYA, C. (2018). Optimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis. Energy, 163, 1017–1031. https://doi.org/10.1016/j.energy.2018.08.140
  • FATTAHI, R., & KHALILZADEH, M. (2018). Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment. Safety Science, 102, 290–300. https://doi.org/10.1016/j.ssci.2017.10.018
  • FU, Y. K. (2019). An integrated approach to catering supplier selection using AHP-ARAS-MCGP methodology. Journal of Air Transport Management, 75, 164–169. https://doi.org/10.1016/j.jairtraman.2019.01.011
  • GAN, J., ZHONG, S., LIU, S., & YANG, D. (2019). Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment. Discrete Dynamics in Nature and Society, 2019, 2456260. https://doi.org/10.1155/2019/2456260
  • GHENAI, C., ALBAWAB, M., & BETTAYEB, M. (2020). Sustainability indicators for renewable energy systems using multi-criteria decision-making model and extended SWARA/ARAS hybrid method. Renewable Energy, 146, 580–597. https://doi.org/10.1016/j.renene.2019.06.157
  • GHIMIRE, L. P., & KIM, Y. (2018). An analysis on barriers to renewable energy development in the context of Nepal using AHP. Renewable Energy, 129, 446–456. https://doi.org/10.1016/j.renene.2018.06.011
  • GOVINDAN, K., & SIVAKUMAR, R. (2016). Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches. Annals of Operations Research, 238(1), 243–276. https://doi.org/10.1007/s10479-015-2004-4
  • HALDAR, A., RAY, A., BANERJEE, D., & GHOSH, S. (2012). A hybrid MCDM model for resilient supplier selection. International Journal of Management Science and Engineering Management, 7(4), 284–292. https://doi.org/10.1080/17509653.2012.10671234
  • HOSSEINI, S., & KHALED, A. Al. (2019). A Hybrid Ensemble and AHP Approach for Resilient Supplier Selection. J. Intell. Manuf., 30(1), 207–228. https://doi.org/10.1007/s10845-016-1241-y
  • IGHRAVWE, D. E., & OKE, S. A. (2019). A multi-criteria decision-making framework for selecting a suitable maintenance strategy for public buildings using sustainability criteria. Journal of Building Engineering, 24, 100753. https://doi.org/10.1016/j.jobe.2019.100753
  • ILBAHAR, E., KARAŞAN, A., CEBI, S., & KAHRAMAN, C. (2018). A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Safety Science, 103, 124–136. https://doi.org/10.1016/j.ssci.2017.10.025
  • IVANOV, D. (2018). New Drivers for Supply Chain Structural Dynamics and Resilience: Sustainability, Industry 4.0, Self-Adaptation BT - Structural Dynamics and Resilience in Supply Chain Risk Management. Içinde D. Ivanov (Ed.), Structural Dynamics and Resilience in Supply Chain Risk Management (ss. 293–313). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-69305-7_10
  • JAIN, V., SANGAIAH, A. K., SAKHUJA, S., THODUKA, N., & AGGARWAL, R. (2018). Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry. Neural Computing and Applications, 29(7), 555–564. https://doi.org/10.1007/s00521-016-2533-z
  • KABAK, M., ERBAŞ, M., ÇETINKAYA, C., & ÖZCEYLAN, E. (2018). A GIS-based MCDM approach for the evaluation of bike-share stations. Journal of Cleaner Production, 201, 49–60. https://doi.org/10.1016/j.jclepro.2018.08.033
  • KERŠULIENE, V., & TURSKIS, Z. (2011). Integrated fuzzy multiple criteria decision making model for architect selection. Technological and Economic Development of Economy, 17(4), 645–666. https://doi.org/10.3846/20294913.2011.635718
  • KPMG Türkiye. (2020). Covid-19’un Tedarik Zinciri Üzerindeki Etkilerini Yönetmek Için Olası Stratejik Hamleler. Tarihinde adresinden erişildi https://assets.kpmg/content/dam/kpmg/tr/pdf/2020/03/covid-19-tedarik-zinciri.pdf
  • KRAUSE, D. R., VACHON, S., & ROBERT D., K. (2009). Special Topic Forum on Sustainable Supply Chain Management: Introduction and Reflections on the Role of Purchasing Management. Journal of Supply Chain Management, 45(4), 18–25. https://doi.org/10.1111/j.1745-493X.2009.03173.x
  • KÜÇÜK, O., & ECER, F. (2010). İmalatçı İşletmelerde Uygun Tedarikçi Seçimi: Analitik Hiyerarşi Yöntemi İle Bir Kobi Uygulaması. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 22(2), 435–450.
  • KUO, R. J., WANG, Y. C., & TIEN, F. C. (2010). Integration of artificial neural network and MADA methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161–1170. https://doi.org/10.1016/J.JCLEPRO.2010.03.020
  • LEE, A. H. I. (2009). A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks. Expert Systems with Applications, 36(2), 2879–2893. https://doi.org/10.1016/j.eswa.2008.01.045
  • LIN, H.-F. (2010). An application of fuzzy AHP for evaluating course website quality. Computers & Education, 54(4), 877–888. https://doi.org/10.1016/J.COMPEDU.2009.09.017
  • LUTHRA, S., & MANGLA, S. K. (2018). Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Safety and Environmental Protection, 117, 168–179. https://doi.org/10.1016/j.psep.2018.04.018
  • LYU, H. M., SUN, W. J., SHEN, S. L., & ARULRAJAH, A. (2018). Flood risk assessment in metro systems of mega-cities using a GIS-based modeling approach. Science of the Total Environment, 626, 1012–1025. https://doi.org/10.1016/j.scitotenv.2018.01.138
  • MADENOĞLU, F. S. (2020). Personnel Selection By Using Fuzzy Hybrid Multi Criteria Decision Making Methodology. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 8(3), 953–962. https://doi.org/10.18506/anemon.645838
  • MATIĆ, B., JOVANOVIĆ, S., DAS, D. K., ZAVADSKAS, E. K., STEVIĆ, Ž., SREMAC, S., & MARINKOVIĆ, M. (2019). A New Hybrid MCDM Model: Sustainable Supplier Selection in a Construction Company. Symmetry, 11(3), 353. https://doi.org/10.3390/sym11030353
  • MAVI, R. K. (2015). Green supplier selection: A fuzzy AHP and fuzzy ARAS approach. International Journal of Services and Operations Management, 22(2), 165–188. https://doi.org/10.1504/IJSOM.2015.071528
  • MEDINECKIENE, M., ZAVADSKAS, E. K., BJÖRK, F., & TURSKIS, Z. (2015). Multi-criteria decision-making system for sustainable building assessment/certification. Archives of Civil and Mechanical Engineering, 15(1), 11–18. https://doi.org/10.1016/j.acme.2014.09.001
  • MOHEB-ALIZADEH, H., MAHMOUDI, M., & BAGHERI, R. (2017). Supplier selection and order allocation using a stochastic multi-objective programming model and genetic algorithm. International Journal of Integrated Supply Management, 11(4), 291–315. https://doi.org/10.1504/IJISM.2017.089849
  • MOSTAFAEIPOUR, A., HOSSEINI DEHSHIRI, S. J., & HOSSEINI DEHSHIRI, S. S. (2020). Ranking locations for producing hydrogen using geothermal energy in Afghanistan. International Journal of Hydrogen Energy, 45(32), 15924–15940. https://doi.org/10.1016/j.ijhydene.2020.04.079
  • NAZARI, S., FALLAH, M., KAZEMIPOOR, H., & SALEHIPOUR, A. (2018). A fuzzy inference- fuzzy analytic hierarchy process-based clinical decision support system for diagnosis of heart diseases. Expert Systems with Applications, 95, 261–271. https://doi.org/10.1016/j.eswa.2017.11.001
  • ORUÇ, K. O. (2019). Bulanık Analitik Hiyerarşi Süreci ve Bulanık Aras Yöntemleri Ile Polis Merkezi Kuruluş Yeri Seçimi: Isparta Örneği. Içinde Suleyman Demirel University The Journal of Faculty of Economics and Administrative Sciences Y.2019 (C. 24). Tarihinde adresinden erişildi https://orcid.org/0000-0002-0716-
  • ÖZTÜRK, M., & PAKSOY, T. (2020). Tedarikçi seçimi için yeni bir aralık tip-2 hibrit bulanık kural tabanlı AHP sistemi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 35(3), 1519–1535. https://doi.org/10.17341/gazimmfd.494086
  • PAMUČAR, D., STEVIĆ, Ž., & ZAVADSKAS, E. K. (2018). Integration of interval rough AHP and interval rough MABAC methods for evaluating university web pages. Applied Soft Computing Journal, 67, 141–163. https://doi.org/10.1016/j.asoc.2018.02.057
  • PETROVIĆ, G., MIHAJLOVIĆ, J., ĆOJBAŠIĆ, Ž., MADIĆ, M., & MARINKOVIĆ, D. (2019). Comparison of three fuzzy MCDM methods for solving the supplier selection problem. Facta Universitatis, Series: Mechanical Engineering, 17(3), 455–469. https://doi.org/10.22190/FUME190420039P
  • PRAMANIK, D., HALDAR, A., MONDAL, S. C., NASKAR, S. K., & RAY, A. (2017). Resilient supplier selection using AHP-TOPSIS-QFD under a fuzzy environment. International Journal of Management Science and Engineering Management, 12(1), 45–54. https://doi.org/10.1080/17509653.2015.1101719
  • PwC Türkiye. (2020). COVID-19: Operasyonlar ve Tedarik Zinciri Etkisi. Tarihinde adresinden erişildi https://www.pwc.com.tr/tr/Hizmetlerimiz/danismanlik/tedarik-zinciri-yonetimi/covid-19-operasyonlar-ve-tedarik-zinciri-etkisi.pdf
  • RAJESH, R., & RAVI, V. (2015). Supplier selection in resilient supply chains: a grey relational analysis approach. Journal of Cleaner Production, 86, 343–359. https://doi.org/https://doi.org/10.1016/j.jclepro.2014.08.054
  • REN, C., LI, Z., & ZHANG, H. (2019). Integrated multi-objective stochastic fuzzy programming and AHP method for agricultural water and land optimization allocation under multiple uncertainties. Journal of Cleaner Production, 210, 12–24. https://doi.org/10.1016/j.jclepro.2018.10.348
  • SENNAROGLU, B., & VARLIK CELEBI, G. (2018). A military airport location selection by AHP integrated PROMETHEE and VIKOR methods. Transportation Research Part D: Transport and Environment, 59, 160–173. https://doi.org/10.1016/j.trd.2017.12.022
  • SIRISAWAT, P., & KIATCHAROENPOL, T. (2018). Fuzzy AHP-TOPSIS approaches to prioritizing solutions for reverse logistics barriers. Computers and Industrial Engineering, 117, 303–318. https://doi.org/10.1016/j.cie.2018.01.015
  • SOLANGI, Y. A., TAN, Q., MIRJAT, N. H., & ALI, S. (2019). Evaluating the strategies for sustainable energy planning in Pakistan: An integrated SWOT-AHP and Fuzzy-TOPSIS approach. Journal of Cleaner Production, 236, 117655. https://doi.org/10.1016/j.jclepro.2019.117655
  • ŠTREIMIKIENE, D., ŠLIOGERIENE, J., & TURSKIS, Z. (2016). Multi-criteria analysis of electricity generation technologies in Lithuania. Renewable Energy, 85, 148–156. https://doi.org/10.1016/j.renene.2015.06.032
  • TIAN, G., ZHANG, H., FENG, Y., WANG, D., PENG, Y., & JIA, H. (2018, Ocak 1). Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method. Renewable and Sustainable Energy Reviews, C. 81, ss. 682–692. Elsevier Ltd. https://doi.org/10.1016/j.rser.2017.08.050
  • TORABI, S. A., BAGHERSAD, M., & MANSOURI, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 79, 22–48. https://doi.org/https://doi.org/10.1016/j.tre.2015.03.005
  • TURSKIS, Z., & ZAVADSKAS, E. K. (2010). A new fuzzy additive ratio assessment method (ARAS‐F). Case study: The analysis of fuzzy multiple criteria in order to select the logistic centers location. Transport, 25(4), 423–432. https://doi.org/10.3846/transport.2010.52
  • VALIPOUR PARKOUHI, S., & SAFAEI GHADIKOLAEI, A. (2017). A resilience approach for supplier selection: Using Fuzzy Analytic Network Process and grey VIKOR techniques. Journal of Cleaner Production, 161, 431–451. https://doi.org/10.1016/J.JCLEPRO.2017.04.175
  • VUGRIN, E. D., WARREN, D. E., & EHLEN, M. A. (2011). A resilience assessment framework for infrastructure and economic systems: Quantitative and qualitative resilience analysis of petrochemical supply chains to a hurricane. Process Safety Progress, 30(3), 280–290. https://doi.org/10.1002/prs.10437
  • WANG, B., SONG, J., REN, J., LI, K., DUAN, H., & WANG, X. (2019). Selecting sustainable energy conversion technologies for agricultural residues: A fuzzy AHP-VIKOR based prioritization from life cycle perspective. Resources, Conservation and Recycling, 142, 78–87. https://doi.org/10.1016/j.resconrec.2018.11.011
  • ZAVADSKAS, E. K., TURSKIS, Z., & VILUTIENE, T. (2010). Multiple criteria analysis of foundation instalment alternatives by applying Additive Ratio Assessment (ARAS) method. Archives of Civil and Mechanical Engineering, 10(3), 123–141. https://doi.org/10.1016/S1644-9665(12)60141-1
Toplam 68 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Ahmet Çalık 0000-0002-6796-0052

Yayımlanma Tarihi 30 Ekim 2022
Kabul Tarihi 25 Mart 2021
Yayımlandığı Sayı Yıl 2022

Kaynak Göster

APA Çalık, A. (2022). Bulanık AHP-Bulanık ARAS Yöntemlerine Dayalı Dayanıklı Tedarikçi Seçimi. İstanbul Gelişim Üniversitesi Sosyal Bilimler Dergisi, 9(2), 275-296. https://doi.org/10.17336/igusbd.798775

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