Multi-criteria decision making for green supplier selection using interval type-2 fuzzy AHP: a case study of a home appliance manufacturer
暂无分享,去创建一个
[1] Ali Bozorgi-Amiri,et al. A novel interval type-2 fuzzy evaluation model based group decision analysis for green supplier selection problems: A case study of battery industry , 2017 .
[2] R. Handfield,et al. ‘Green’ value chain practices in the furniture industry , 1997 .
[3] Hoang Pham,et al. A fuzzy rule-based generation algorithm in interval type-2 fuzzy logic system for fault prediction in the early phase of software development , 2018, J. Exp. Theor. Artif. Intell..
[4] Gwo-Hshiung Tzeng,et al. New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management , 2016 .
[5] Huiru Zhao,et al. Selecting Green Supplier of Thermal Power Equipment by Using a Hybrid MCDM Method for Sustainability , 2014 .
[6] M. Tseng,et al. A literature review on green supply chain management: Trends and future challenges , 2019, Resources, Conservation and Recycling.
[7] Morteza Yazdani,et al. An integrated MCDM approach to green supplier selection , 2014 .
[8] Ali Nazari,et al. Prediction compressive strength of Portland cement-based geopolymers by artificial neural networks , 2012, Neural Computing and Applications.
[9] Jianhua Ma,et al. Novel green supplier selection method by combining quality function deployment with partitioned Bonferroni mean operator in interval type-2 fuzzy environment , 2019, Inf. Sci..
[10] Javad Sadeghi,et al. Evaluating a green supplier selection problem using a hybrid MODM algorithm , 2017, J. Intell. Manuf..
[11] Gülçin Büyüközkan,et al. A Fuzzy MCDM Approach to Evaluate Green Suppliers , 2011 .
[12] Huayou Chen,et al. An integrated approach to green supplier selection based on the interval type-2 fuzzy best-worst and extended VIKOR methods , 2019, Inf. Sci..
[13] Erkan Celik,et al. An Integrated Best-Worst and Interval Type-2 Fuzzy TOPSIS Methodology for Green Supplier Selection , 2018, Mathematics.
[14] Changyong Liang,et al. An intuitionsitic fuzzy judgement matrix and TOPSIS integrated multi-criteria decision making method for green supplier selection , 2015, J. Intell. Fuzzy Syst..
[15] Hamed Mohammadi,et al. Green supplier selection by developing a new group decision-making method under type 2 fuzzy uncertainty , 2017 .
[16] Jurgita Antucheviciene,et al. A new multi-criteria model based on interval type-2 fuzzy sets and EDAS method for supplier evaluation and order allocation with environmental considerations , 2017, Comput. Ind. Eng..
[17] E. Celik,et al. An interval type-2 fuzzy QUALIFLEX approach to measure performance effectiveness of ballast water treatment (BWT) system on-board ship , 2018, Ships and Offshore Structures.
[18] Shyi-Ming Chen,et al. Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval type-2 fuzzy sets , 2008, 2008 International Conference on Machine Learning and Cybernetics.
[19] Hani Hagras,et al. A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots , 2004, IEEE Transactions on Fuzzy Systems.
[20] Jerry M. Mendel,et al. Interval type-2 fuzzy logic systems , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).
[21] Alev Taskin Gumus,et al. A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management , 2014, J. Intell. Fuzzy Syst..
[22] Anjali Awasthi,et al. Green supplier development program selection using NGT and VIKOR under fuzzy environment , 2016, Comput. Ind. Eng..
[23] Jerry M. Mendel,et al. Uncertainty, fuzzy logic, and signal processing , 2000, Signal Process..
[24] He-Yau Kang,et al. A green supplier selection model for high-tech industry , 2009, Expert Syst. Appl..
[25] Dongrui Wu,et al. Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers , 2006, Eng. Appl. Artif. Intell..
[26] K. Mathiyazhagan,et al. Modeling the criteria for selection of suppliers towards green aspect: a case in Indian automobile industry , 2018 .
[27] Lotfi A. Zadeh,et al. The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..
[28] İhsan Kaya,et al. Investment project evaluation by a decision making methodology based on type-2 fuzzy sets , 2015, Appl. Soft Comput..
[29] Zhu-jiance,et al. Study on the Determining and Importance Sequence of Factors affecting GSCM , 2012, ICSSSM 2012.
[30] Alejandro Sobrino,et al. Designing a system to extract and interpret timed causal sentences in medical reports , 2018, J. Exp. Theor. Artif. Intell..
[31] Ali H. Diabat,et al. A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences , 2013 .
[32] Stephen J. Walters,et al. Quality of life outcomes in clinical trials and health-care evaluation , 2009 .
[33] R. K. Mavi,et al. Identification and Assessment of Logistical Factors to Evaluate a Green Supplier Using the Fuzzy Logic DEMATEL Method , 2013 .
[34] Cengiz Kahraman,et al. Fuzzy analytic hierarchy process with interval type-2 fuzzy sets , 2014, Knowl. Based Syst..
[35] Erkan Celik,et al. An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: The case of ship loader , 2018 .
[36] Erkan Kose,et al. Green supplier selection based on IFS and GRA , 2013, Grey Syst. Theory Appl..
[37] Fatih Ecer,et al. An integrated Fuzzy AHP and ARAS model to evaluate mobile banking services , 2017 .
[38] Narges Banaeian,et al. Criteria definition and approaches in green supplier selection – a case study for raw material and packaging of food industry , 2015 .
[39] Lazim Abdullah,et al. A new type-2 fuzzy set of linguistic variables for the fuzzy analytic hierarchy process , 2014, Expert Syst. Appl..
[40] Lakshman S. Thakur,et al. Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain , 2012, Expert Syst. Appl..
[41] Morteza Yazdani,et al. New integration of MCDM methods and QFD in the selection of green suppliers , 2016 .
[42] Özer Uygun,et al. Performance evaluation of green supply chain management using integrated fuzzy multi-criteria decision making techniques , 2016, Comput. Ind. Eng..
[43] Siba Sankar Mahapatra,et al. Evaluation and selection of suppliers considering green perspectives , 2016 .
[44] Fatih Ecer,et al. AHP-VIKOR ENTEGRE YÖNTEMİ İLE TEDARİKÇİ SEÇİMİ: TEKSTİL SEKTÖRÜ UYGULAMASI , 2016 .
[45] Arunodaya Raj Mishra,et al. A novel hesitant fuzzy WASPAS method for assessment of green supplier problem based on exponential information measures , 2019, Journal of Cleaner Production.
[46] Ali Diabat,et al. An exploration of green supply chain practices and performances in an automotive industry , 2013 .
[47] Ualison Rébula de Oliveira,et al. A systematic literature review on green supply chain management: Research implications and future perspectives , 2018, Journal of Cleaner Production.
[48] Eleonora Bottani,et al. A QFD-ANP Method for Supplier Selection with Benefits, Opportunities, Costs and Risks Considerations , 2018, Int. J. Inf. Technol. Decis. Mak..
[49] Mehdi Keshavarz Ghorabaee. Developing an MCDM method for robot selection with interval type-2 fuzzy sets , 2016 .
[50] Anil S. Dube,et al. Analysis of green supply chain barriers using integrated ISM-fuzzy MICMAC approach , 2016 .
[51] Charbel José Chiappetta Jabbour,et al. Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company , 2014, Eur. J. Oper. Res..
[52] Xinwang Liu,et al. An interval type-2 fuzzy TOPSIS model for large scale group decision making problems with social network information , 2018, Inf. Sci..
[53] Gülçin Büyüközkan,et al. A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers , 2012, Expert Syst. Appl..
[54] Mehmet Ali Ilgin,et al. A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT , 2018, Expert Syst. Appl..
[55] Temitope Raphael Ayodele,et al. A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria , 2018, Applied Energy.
[56] Shyi-Ming Chen,et al. Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method , 2010, Expert Syst. Appl..
[57] Chin-Nung Liao,et al. Integrated FAHP, ARAS-F and MSGP methods for green supplier evaluation and selection , 2015 .
[58] Maghsud Solimanpur,et al. Supplier selection and order allocation using two-stage hybrid supply chain model and game-based order price , 2019, Operational Research.
[59] Fatih Ecer,et al. İMALATÇI İŞLETMELERDE UYGUN TEDARİKÇİ SEÇİMİ: ANALİTİK HİYERARŞİ YÖNTEMİ İLE BİR KOBİ UYGULAMASI , 2010 .
[60] Edmundas Kazimieras Zavadskas,et al. Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets , 2016 .
[61] Witold Pedrycz,et al. An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment , 2017, Eur. J. Oper. Res..
[62] Kannan Govindan,et al. Application of fuzzy VIKOR for evaluation of green supply chain management practices , 2015 .
[63] Alev Taskin Gumus,et al. A New Extension of the ELECTRE Method Based Upon Interval Type-2 Fuzzy Sets for Green Logistic Service Providers Evaluation , 2016 .
[64] Kannan Govindan,et al. Multi criteria decision making approaches for green supplier evaluation and selection: a literature review , 2015 .
[65] Jerry M. Mendel,et al. Type-2 fuzzy sets made simple , 2002, IEEE Trans. Fuzzy Syst..
[66] A. Niewiadomski,et al. Interval-valued linguistic summaries of databases , 2006 .
[67] Lazim Abdullah,et al. A new DEMATEL method based on interval type-2 fuzzy sets for developing causal relationship of knowledge management criteria , 2019, Neural Computing and Applications.
[68] Fatih Ecer,et al. A hybrid banking websites quality evaluation model using AHP and COPRAS-G: a Turkey case , 2014 .
[69] J. Mendel. Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions , 2001 .
[70] Qingyun Zhu,et al. Organizational Green Supply Chain Management Capability Assessment: A Hybrid Group Decision Making Model Application , 2018, IEEE Engineering Management Review.
[71] Mahdi Mahmoodi,et al. A New Fuzzy TOPSIS-TODIM Hybrid Method for Green Supplier Selection Using Fuzzy Time Function , 2014, Adv. Fuzzy Syst..
[72] Georgios N. Aretoulis,et al. Construction material supplier selection under multiple criteria , 2010, Oper. Res..
[73] F. Ecer,et al. DETERMINATION OF THE FINANCIAL SUPPORT REQUIRED BY THE FAMILIES WITH DISABILITIES TO ACHIEVE STANDARD LIFE CONDITIONS WITH THE AHP METHOD , 2018, Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi.
[74] Abraham Mendoza,et al. Modeling actual transportation costs in supplier selection and order quantity allocation decisions , 2013, Oper. Res..
[75] G. Bruno,et al. Greener supplier selection: state of the art and some empirical evidence , 2013 .
[76] Ravi Kant,et al. Green supply chain management (GSCM): a structured literature review and research implications , 2015 .
[77] Stephen J. Walters,et al. Quality of Life Outcomes in Clinical Trials and Health-Care Evaluation: A Practical Guide to Analysis and Interpretation , 2009 .
[78] Cengiz Kahraman,et al. Interval Type-2 FAHP: A Multicriteria Wind Turbine Selection , 2017 .
[79] Gwo-Hshiung Tzeng,et al. A hybrid MCDM approach for improving the performance of green suppliers in the TFT-LCD industry , 2015 .
[80] Umang Soni,et al. Green supplier selection using multi-criterion decision making under fuzzy environment: A case study in automotive industry , 2019, Comput. Ind. Eng..
[81] Chunqiao Tan,et al. A New Extension to a Multi-Criteria Decision-Making Model for Sustainable Supplier Selection under an Intuitionistic Fuzzy Environment , 2019, Sustainability.
[82] Lucila Maria de Souza Campos,et al. Performance evaluation of green suppliers using entropy-TOPSIS-F , 2019, Journal of Cleaner Production.