A q-rung orthopair fuzzy multi-criteria group decision making method for supplier selection based on a novel distance measure

Supplier selection and evaluation is a crucial decision-making issue to establish an effective supply chain. Higher-order fuzzy decision-making methods have become powerful tools to support decision-makers in solving their problems effectively by reflecting uncertainty in calculations better than crisp sets in the last 3 decades. The q-rung orthopair fuzzy (q-ROF) sets which are the general form of both intuitionistic and Pythagorean fuzzy sets, have been recently introduced to provide decision-makers more freedom of expression than other fuzzy sets. In this paper, we introduce q-ROF TOPSIS and q-ROF ELECTRE as two separate methods and new approaches for group decision making to select the best supplier. As the existing distance measures in q-rung orthopair fuzzy environment have some drawbacks and generate counter-intuitive results, we propose a new distance measure along with its proofs to use in both q-ROF TOPSIS and q-ROF ELECTRE methods. Moreover, a comparison study is conducted to illustrate the superiority of the proposed distance measure. Subsequently, a comprehensive case study is performed with q-ROF TOPSIS and q-ROF ELECTRE methods separately to choose the best supplier for a construction company by rating the importance of criteria and alternatives under q-ROF environment. Finally, a comparison and parameter analysis are performed among the proposed q-ROF TOPSIS and q-ROF ELECTRE methods and existing q-ROF decision-making methods to demonstrate the effectiveness of our proposed methods.

[1]  Weiqiong Wang,et al.  Distance measure between intuitionistic fuzzy sets , 2005, Pattern Recognit. Lett..

[2]  Dug Hun Hong,et al.  A Note on Similarity Measures between Vague Sets and between Elements , 1999, Inf. Sci..

[3]  Dragan Simic,et al.  50 years of fuzzy set theory and models for supplier assessment and selection: A literature review , 2017, J. Appl. Log..

[4]  A. Noorul Haq,et al.  Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model , 2006 .

[5]  Wen Sheng Du,et al.  Minkowski‐type distance measures for generalized orthopair fuzzy sets , 2018, Int. J. Intell. Syst..

[6]  Mahdi Karbasian,et al.  The application of ISM model in evaluating agile suppliers selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods , 2015, Expert Syst. Appl..

[7]  Guiwu Wei,et al.  Similarity Measures of q-Rung Orthopair Fuzzy Sets Based on Cosine Function and Their Applications , 2019, Mathematics.

[8]  Kun-Tzu Yu,et al.  Strategic Vender Selection Criteria , 2013, ITQM.

[9]  Przemyslaw Grzegorzewski,et al.  Distances between intuitionistic fuzzy sets and/or interval-valued fuzzy sets based on the Hausdorff metric , 2004, Fuzzy Sets Syst..

[10]  Rajkumar Verma,et al.  On Generalized Intuitionistic Fuzzy Divergence (Relative Information) and Their Properties , 2012 .

[11]  Gary W. Dickson,et al.  AN ANALYSIS OF VENDOR SELECTION SYSTEMS AND DECISIONS , 1966 .

[12]  Shyi-Ming Chen,et al.  Measures of similarity between vague sets , 1995, Fuzzy Sets Syst..

[13]  Zeshui Xu,et al.  Some new similarity measures for intuitionistic fuzzy values and their application in group decision making , 2010 .

[14]  Kai Wang,et al.  A group decision making sustainable supplier selection approach using extended TOPSIS under interval-valued Pythagorean fuzzy environment , 2019, Expert Syst. Appl..

[15]  Ronald R. Yager,et al.  Lexicographic Orders of Intuitionistic Fuzzy Values and Their Relationships , 2019, Mathematics.

[16]  Lin Liu,et al.  Information measures for q‐rung orthopair fuzzy sets , 2019, Int. J. Intell. Syst..

[17]  Ronald R. Yager,et al.  Generalized Orthopair Fuzzy Sets , 2017, IEEE Transactions on Fuzzy Systems.

[18]  Li Dengfeng,et al.  New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions , 2002, Pattern Recognit. Lett..

[19]  Ting-Yu Chen,et al.  A note on distances between intuitionistic fuzzy sets and/or interval-valued fuzzy sets based on the Hausdorff metric , 2007, Fuzzy Sets Syst..

[20]  E. Wilson,et al.  The Relative Importance of Supplier Selection Criteria: A Review and Update , 1994 .

[21]  Rajkumar Verma,et al.  A new measure of inaccuracy with its application to multi-criteria decision making under intuitionistic fuzzy environment , 2014, J. Intell. Fuzzy Syst..

[22]  Zeshui Xu,et al.  Intuitionistic and interval-valued intutionistic fuzzy preference relations and their measures of similarity for the evaluation of agreement within a group , 2009, Fuzzy Optim. Decis. Mak..

[23]  Rajkumar Verma,et al.  On generalized similarity measures for Pythagorean fuzzy sets and their applications to multiple attribute decision‐making , 2019, Int. J. Intell. Syst..

[24]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[25]  Lori Tavasszy,et al.  Supplier selection in the airline retail industry using a funnel methodology: Conjunctive screening method and fuzzy AHP , 2014, Expert Syst. Appl..

[26]  Edmundas Kazimieras Zavadskas,et al.  Decision Making Methods Based on Fuzzy Aggregation Operators: Three Decades Review from 1986 to 2017 , 2018, Int. J. Inf. Technol. Decis. Mak..

[27]  Z. S. Xu,et al.  An Overview of Distance and Similarity Measures of Intuitionistic Fuzzy Sets , 2008, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[28]  Chen-Tung Chen,et al.  A fuzzy approach for supplier evaluation and selection in supply chain management , 2006 .

[29]  Mark A. Vonderembse,et al.  The Impact of Supplier Selection Criteria and Supplier Involvement on Manufacturing Performance , 1999 .

[30]  Honghai Wang,et al.  Multi‐attribute group decision‐making methods based on q‐rung orthopair fuzzy linguistic sets , 2019, Int. J. Intell. Syst..

[31]  Ronald R. Yager,et al.  Another View on Generalized Intuitionistic Fuzzy Soft Sets and Related Multiattribute Decision Making Methods , 2019, IEEE Transactions on Fuzzy Systems.

[32]  Jun Ye,et al.  Cosine similarity measures for intuitionistic fuzzy sets and their applications , 2011, Math. Comput. Model..

[33]  Diyar Akay,et al.  A biparametric similarity measure on intuitionistic fuzzy sets with applications to pattern recognition , 2014, Inf. Sci..

[34]  Wenyi Zeng,et al.  Distance Measure of Pythagorean Fuzzy Sets , 2018, Int. J. Intell. Syst..

[35]  H. B. Mitchell,et al.  On the Dengfeng-Chuntian similarity measure and its application to pattern recognition , 2003, Pattern Recognit. Lett..

[36]  Miin-Shen Yang,et al.  Similarity measures of intuitionistic fuzzy sets based on Hausdorff distance , 2004, Pattern Recognit. Lett..

[37]  Krassimir T. Atanassov,et al.  An equality between intuitionistic fuzzy sets , 1996, Fuzzy Sets Syst..

[38]  Rui Wang,et al.  A Novel Approach for Green Supplier Selection under a q-Rung Orthopair Fuzzy Environment , 2018, Symmetry.

[39]  Hui Gao,et al.  Some q‐rung orthopair fuzzy Heronian mean operators in multiple attribute decision making , 2018, Int. J. Intell. Syst..

[40]  Mustafa Jahangoshai Rezaee,et al.  Evaluation and selection of sustainable suppliers in supply chain using new GP-DEA model with imprecise data , 2018 .

[41]  Zeshui Xu,et al.  Extension of TOPSIS to Multiple Criteria Decision Making with Pythagorean Fuzzy Sets , 2014, Int. J. Intell. Syst..

[42]  Yan De,et al.  Similarity Measures between Vague Sets , 2006 .

[43]  Chin-Teng Lin,et al.  A New Method for Intuitionistic Fuzzy Multiattribute Decision Making , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[44]  Kevin Cullinane,et al.  A comparison of fuzzy DEA and fuzzy TOPSIS in sustainable supplier selection: Implications for sourcing strategy , 2019, Expert Syst. Appl..

[45]  Naif Alajlan,et al.  Approximate reasoning with generalized orthopair fuzzy sets , 2017, Inf. Fusion.

[46]  S. Farid Mousavi,et al.  Group decision making process for supplier selection with VIKOR under fuzzy environment , 2010, Expert Syst. Appl..

[47]  W. C. Benton,et al.  Vendor selection criteria and methods , 1991 .

[48]  Janusz Kacprzyk,et al.  Distances between intuitionistic fuzzy sets , 2000, Fuzzy Sets Syst..

[49]  Mohammad Reza Akbari Jokar,et al.  Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method , 2019, Journal of Manufacturing Systems.

[50]  Zeshui Xu,et al.  Information fusion for intuitionistic fuzzy decision making: An overview , 2016, Information Fusion.

[51]  Pengfei Shi,et al.  Similarity measures on intuitionistic fuzzy sets , 2003, Pattern Recognit. Lett..

[52]  Ting-Yu Chen,et al.  The ELECTRE multicriteria analysis approach based on Atanassov's intuitionistic fuzzy sets , 2011, Expert Syst. Appl..

[53]  Ronald R. Yager,et al.  Pythagorean Membership Grades in Multicriteria Decision Making , 2014, IEEE Transactions on Fuzzy Systems.

[54]  Diyar Akay,et al.  A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method , 2009, Expert Syst. Appl..

[55]  Shuo-Yan Chou,et al.  A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach , 2008, Expert Syst. Appl..

[56]  Peng Wang,et al.  Some q‐Rung Orthopair Fuzzy Aggregation Operators and their Applications to Multiple‐Attribute Decision Making , 2018, Int. J. Intell. Syst..