Novel Aczel–Alsina operations-based hesitant fuzzy aggregation operators and their applications in cyclone disaster assessment

As a fuzzy set (FS) expansion, the hesitant fuzzy set (HFS) is successfully employed to demonstrate circumstances where it is admissible to ascertain a few potential membership degrees (MDs) of a component in a set because of the uncertainty between various values. Considering that there is still no research on Aczel–Alsina triangular norms and conorms in a hesitant fuzzy (HF) environment, in this article we introduce for the first time, Aczel–Alsina operations on HFSs. Then, based on these operations, we originate a few new aggregation operators for aggregating HF information namely HF Aczel–Alsina weighted averaging (HFAAWA) operator, HF Aczel–Alsina ordered weighted averaging (HFAAOWA) operator, HF Aczel–Alsina hybrid averaging (HFAAHA) operator, HF Aczel–Alsina weighted geometric (HFAAWG) operator, HF Aczel–Alsina ordered weighted geometric (HFAAOWG) operator, HF Aczel–Alsina hybrid geometric (HFAAHG) operator and HF Aczel–Alsina weighted Bonferroni mean (HFAAWBM) operator. Some essential characteristics of those suggested operators are shown, and the interrelatedness between them is displayed exhaustively. Then, we take advantage of those operators to produce a methodology to interpret the HF multiple attribute decision making (MADM) difficulties. We present a functional model for cyclone disaster assessment to certify the produced approaches and to establish their effectiveness and practicality. Further, we conduct comparison analysis for the legitimacy of our produced methodologies.

[1]  R. Mesiar,et al.  Novel Aczel–Alsina operations‐based interval‐valued intuitionistic fuzzy aggregation operators and their applications in multiple attribute decision‐making process , 2021, Int. J. Intell. Syst..

[2]  R. Yager,et al.  Aczel–Alsina aggregation operators and their application to intuitionistic fuzzy multiple attribute decision making , 2021, Int. J. Intell. Syst..

[3]  R. Yager,et al.  Hybridizations of generalized Dombi operators and Bonferroni mean operators under dual probabilistic linguistic environment for group decision‐making , 2021, Int. J. Intell. Syst..

[4]  Amjad Hussain,et al.  Analysis of Social Networks by Using Pythagorean Cubic Fuzzy Einstein Weighted Geometric Aggregation Operators , 2021 .

[5]  Samarjit Kar,et al.  Some new hybrid hesitant fuzzy weighted aggregation operators based on Archimedean and Dombi operations for multi-attribute decision making , 2021, Neural Computing and Applications.

[6]  Ying-Ming Wang,et al.  An extended TODIM approach for group emergency decision making based on bidirectional projection with hesitant triangular fuzzy sets , 2020, Computers & Industrial Engineering.

[7]  Ming Tang,et al.  A Choquet integral-based hesitant fuzzy gained and lost dominance score method for multi-criteria group decision making considering the risk preferences of experts: Case study of higher business education evaluation , 2020, Inf. Fusion.

[8]  Enrique Herrera-Viedma,et al.  A dynamic group decision making process for high number of alternatives using hesitant Fuzzy Ontologies and sentiment analysis , 2020, Knowl. Based Syst..

[9]  Madhumangal Pal,et al.  A novel approach to hesitant multi-fuzzy soft set based decision-making , 2020 .

[10]  Ronald R. Yager,et al.  Fermatean fuzzy sets , 2019, Journal of Ambient Intelligence and Humanized Computing.

[11]  Jiye Liang,et al.  Multi-granularity three-way decisions with adjustable hesitant fuzzy linguistic multigranulation decision-theoretic rough sets over two universes , 2020, Inf. Sci..

[12]  Ronald R. Yager,et al.  Fermatean fuzzy weighted averaging/geometric operators and its application in multi-criteria decision-making methods , 2019, Eng. Appl. Artif. Intell..

[13]  Gagandeep Kaur,et al.  Algorithm for Probabilistic Dual Hesitant Fuzzy Multi-Criteria Decision-Making Based on Aggregation Operators With New Distance Measures , 2018, Mathematics.

[14]  Xiaorong He,et al.  Typhoon disaster assessment based on Dombi hesitant fuzzy information aggregation operators , 2018, Natural Hazards.

[15]  Huchang Liao,et al.  Multiple criteria decision making based on Bonferroni means with hesitant fuzzy linguistic information , 2016, Soft Computing.

[16]  Zeshui Xu,et al.  Generalized Hesitant Fuzzy Harmonic Mean Operators and Their Applications in Group Decision Making , 2015, International Journal of Fuzzy Systems.

[17]  Huchang Liao,et al.  A Multigranularity Linguistic Group Decision‐Making Method Based on Hesitant 2‐Tuple Sets , 2016, Int. J. Intell. Syst..

[18]  Francisco Herrera,et al.  A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making. Towards high quality progress , 2016, Inf. Fusion.

[19]  Huayou Chen,et al.  Hesitant Fuzzy Power Bonferroni Means and Their Application to Multiple Attribute Decision Making , 2015, IEEE Transactions on Fuzzy Systems.

[20]  Huchang Liao,et al.  Extended hesitant fuzzy hybrid weighted aggregation operators and their application in decision making , 2015, Soft Comput..

[21]  Zeshui Xu,et al.  Approaches to manage hesitant fuzzy linguistic information based on the cosine distance and similarity measures for HFLTSs and their application in qualitative decision making , 2015, Expert Syst. Appl..

[22]  Witold Pedrycz,et al.  Hesitant Fuzzy Maclaurin Symmetric Mean Operators and Its Application to Multiple-Attribute Decision Making , 2015, Int. J. Fuzzy Syst..

[23]  Hong-yu Zhang,et al.  An outranking approach for multi-criteria decision-making with hesitant fuzzy linguistic term sets , 2014, Inf. Sci..

[24]  Zeshui Xu,et al.  Some new hybrid weighted aggregation operators under hesitant fuzzy multi-criteria decision making environment , 2014, J. Intell. Fuzzy Syst..

[25]  Dejian Yu,et al.  Some Hesitant Fuzzy Information Aggregation Operators Based on Einstein Operational Laws , 2014, Int. J. Intell. Syst..

[26]  Zeshui Xu,et al.  Hesitant Fuzzy Sets Theory , 2014, Studies in Fuzziness and Soft Computing.

[27]  Qingguo Li,et al.  Multiple Attribute Decision Making Based on Hesitant Fuzzy Einstein Geometric Aggregation Operators , 2014, J. Appl. Math..

[28]  Zeshui Xu,et al.  Hesitant fuzzy Bonferroni means for multi-criteria decision making , 2013, J. Oper. Res. Soc..

[29]  B. Farhadinia,et al.  Information measures for hesitant fuzzy sets and interval-valued hesitant fuzzy sets , 2013, Inf. Sci..

[30]  Zhiming Zhang,et al.  Hesitant fuzzy power aggregation operators and their application to multiple attribute group decision making , 2013, Inf. Sci..

[31]  Guiwu Wei,et al.  Hesitant fuzzy prioritized operators and their application to multiple attribute decision making , 2012, Knowl. Based Syst..

[32]  Francisco Herrera,et al.  Hesitant Fuzzy Linguistic Term Sets for Decision Making , 2012, IEEE Transactions on Fuzzy Systems.

[33]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[34]  Zeshui Xu,et al.  Hesitant fuzzy information aggregation in decision making , 2011, Int. J. Approx. Reason..

[35]  Vicenç Torra,et al.  Hesitant fuzzy sets , 2010, Int. J. Intell. Syst..

[36]  Zeshui Xu,et al.  Projection Models for Intuitionistic Fuzzy Multiple Attribute Decision Making , 2010, Int. J. Inf. Technol. Decis. Mak..

[37]  Ronald R. Yager,et al.  On generalized Bonferroni mean operators for multi-criteria aggregation , 2009, Int. J. Approx. Reason..

[38]  M. J. Frank,et al.  Associative Functions: Triangular Norms And Copulas , 2006 .

[39]  R. Yager ON THE THEORY OF BAGS , 1986 .

[40]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[41]  J. Aczél,et al.  Characterizations of some classes of quasilinear functions with applications to triangular norms and to synthesizing judgements , 1982 .

[42]  K. Menger Statistical Metrics. , 1942, Proceedings of the National Academy of Sciences of the United States of America.

[43]  Tehreem,et al.  Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making , 2021 .

[44]  Wenyi Zeng,et al.  Similarity Measure of Hesitant Fuzzy Sets Based on Implication Function and Clustering Analysis , 2020, IEEE Access.

[45]  Rui Lin,et al.  Model for multiple attribute decision making with hesitant fuzzy information and their application , 2019, Int. J. Knowl. Based Intell. Eng. Syst..

[46]  Zheng Pei,et al.  Operations on Hesitant Linguistic terms sets Induced By Archimedean Triangular Norms And Conorms , 2018, Int. J. Comput. Intell. Syst..

[47]  R. Rodrígueza,et al.  A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making . Towards high quality progress , 2017 .

[48]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[49]  Qingguo Shen,et al.  Dual hesitant fuzzy power aggregation operators based on Archimedean t-conorm and t-norm and their application to multiple attribute group decision making , 2016, Appl. Soft Comput..

[50]  王磊,et al.  Dual hesitant fuzzy power aggregation operators based on Archimedean t-conorm and t-norm and their application to multiple attribute group decision making , 2016 .

[51]  Xiaohong Chen,et al.  Hesitant fuzzy Hamacher aggregation operators for multicriteria decision making , 2015, Appl. Soft Comput..

[52]  Chao Wang,et al.  Induced generalized hesitant fuzzy operators and their application to multiple attribute group decision making , 2014, Comput. Ind. Eng..

[53]  J. Lygeros,et al.  Decision Making I , 2014 .

[54]  Zeshui Xu,et al.  Interval-valued hesitant preference relations and their applications to group decision making , 2013, Knowl. Based Syst..

[55]  Guiwu Wei,et al.  Hesitant Fuzzy Choquet Integral Aggregation Operators and Their Applications to Multiple Attribute Decision Making , 2012 .

[56]  Christian Eitzinger,et al.  Triangular Norms , 2001, Künstliche Intell..

[57]  L. A. ZADEH,et al.  The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..

[58]  Carlo Bonferroni Sulle medie multiple di potenze , 1950 .