A multihesitant fuzzy linguistic multicriteria decision-making approach for logistics outsourcing with incomplete weight information

In selecting logistics service providers, the evaluation criteria can be easily prioritized and possibly interrelated with each other, and the assessment of alternatives under qualitative criteria is usually accomplished by more than one decision maker. A novel multicriteria decision-making approach with multihesitant fuzzy linguistic term elements (MHFLTEs) based on the Heronian mean (HM) and prioritized average operators can effectively deal with the problems inherent in such a scenario. Multihesitant fuzzy linguistic term sets (MHFLTSs) were proposed on the basis of multihesitant fuzzy sets (MHFSs) and hesitant fuzzy linguistic sets (HFLSs), where each MHFLTE can contain nonconsecutive and repeated linguistic terms. Using MHFLTEs, one decision maker can provide one or several consecutive linguistic terms in evaluating an alternative under one specific criterion, different decision makers’ evaluation values can be collected, and the frequency of a linguistic term in the evaluation information can accord with reality. This paper revises the basic operations and comparison method for MHFLTEs on the basis of the originals and defines some multihesitant fuzzy linguistic HM operators for MHFLTEs to deal with problems in which weight information cannot be accurately established for criteria, but their priorities can be provided in groups or without groups. Finally, the validity and effectiveness of the proposed approach are demonstrated through an illustration of a logistics outsourcing problem and a comparison analysis.

[1]  Robert Millen,et al.  Third Party Logistics Services: A Comparison of Experienced American and European Manufacturers , 1993 .

[2]  Zeshui Xu,et al.  Hesitant Fuzzy Linguistic VIKOR Method and Its Application in Qualitative Multiple Criteria Decision Making , 2015, IEEE Transactions on Fuzzy Systems.

[3]  Zeshui Xu,et al.  Distance and similarity measures for hesitant fuzzy linguistic term sets and their application in multi-criteria decision making , 2014, Inf. Sci..

[4]  Na Zhao,et al.  Operators and Comparisons of Hesitant Fuzzy Linguistic Term Sets , 2014, IEEE Transactions on Fuzzy Systems.

[5]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[6]  Jing Wang,et al.  An extended TODIM approach with intuitionistic linguistic numbers , 2018, Int. Trans. Oper. Res..

[7]  James J. H. Liou,et al.  Developing a hybrid multi-criteria model for selection of outsourcing providers , 2010, Expert Syst. Appl..

[8]  Jin-Hsien Wang,et al.  A new version of 2-tuple fuzzy linguistic representation model for computing with words , 2006, IEEE Trans. Fuzzy Syst..

[9]  I. Turksen Type 2 representation and reasoning for CWW , 2002 .

[10]  Hong-yu Zhang,et al.  Multi-criteria Group Decision-Making Approach Based on 2-Tuple Linguistic Aggregation Operators with Multi-hesitant Fuzzy Linguistic Information , 2015, International Journal of Fuzzy Systems.

[11]  Cengiz Kahraman,et al.  Fuzzy Multicriteria Decision-Making: A Literature Review , 2015, Int. J. Comput. Intell. Syst..

[12]  Zhang-peng Tian,et al.  Multi-criteria decision-making based on generalized prioritized aggregation operators under simplified neutrosophic uncertain linguistic environment , 2017, Int. J. Mach. Learn. Cybern..

[13]  Dejian Yu,et al.  Intuitionistic fuzzy geometric Heronian mean aggregation operators , 2013, Appl. Soft Comput..

[14]  Hong-yu Zhang,et al.  Interval-valued hesitant fuzzy linguistic sets and their applications in multi-criteria decision-making problems , 2014, Inf. Sci..

[15]  Li-Jun Yang,et al.  An extension of ELECTRE to multi-criteria decision-making problems with multi-hesitant fuzzy sets , 2015, Inf. Sci..

[16]  Zeshui Xu,et al.  Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets , 2015, Knowl. Based Syst..

[17]  Ronald R. Yager,et al.  Aggregation of ordinal information , 2007, Fuzzy Optim. Decis. Mak..

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

[19]  Shyi-Ming Chen,et al.  Fuzzy decision making based on likelihood-based comparison relations of hesitant fuzzy linguistic term sets and hesitant fuzzy linguistic operators , 2015, Inf. Sci..

[20]  Zeshui Xu,et al.  Heterogeneous multiple criteria group decision making with incomplete weight information: A deviation modeling approach , 2015, Inf. Fusion.

[21]  Luis Martínez-López,et al.  An analysis of symbolic linguistic computing models in decision making , 2013, Int. J. Gen. Syst..

[22]  Aicha Aguezzoul,et al.  Third-party logistics selection problem: A literature review on criteria and methods , 2014 .

[23]  Shaligram Pokharel,et al.  A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider , 2009 .

[24]  Zhibin Wu,et al.  Possibility Distribution-Based Approach for MAGDM With Hesitant Fuzzy Linguistic Information , 2016, IEEE Transactions on Cybernetics.

[25]  Hong-yu Zhang,et al.  Distance-Based Multi-Criteria Group Decision-Making Approaches with Multi-Hesitant Fuzzy Linguistic Information , 2017, Int. J. Inf. Technol. Decis. Mak..

[26]  Jian-qiang Wang,et al.  An outranking method for multi-criteria decision making with duplex linguistic information , 2012, Fuzzy Sets Syst..

[27]  Hong-yu Zhang,et al.  A likelihood-based TODIM approach based on multi-hesitant fuzzy linguistic information for evaluation in logistics outsourcing , 2016, Comput. Ind. Eng..

[28]  Zeshui Xu,et al.  A method based on linguistic aggregation operators for group decision making with linguistic preference relations , 2004, Inf. Sci..

[29]  G. Choquet Theory of capacities , 1954 .

[30]  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.

[31]  Wei-Kai Wang,et al.  An integrated fuzzy approach for provider evaluation and selection in third-party logistics , 2009, Expert Syst. Appl..

[32]  Jianqiang Wang,et al.  An Uncertain Linguistic Multi-criteria Group Decision-Making Method Based on a Cloud Model , 2014, Group Decision and Negotiation.

[33]  Zeshui Xu,et al.  Group decision making based on multiple types of linguistic preference relations , 2008, Inf. Sci..

[34]  Xin Zhang,et al.  Some intuitionistic uncertain linguistic Heronian mean operators and their application to group decision making , 2014, Appl. Math. Comput..

[35]  Dejian Yu,et al.  Hesitant fuzzy prioritized operators and their application in multi-criteria group decision making , 2012 .

[36]  Francisco Herrera,et al.  A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets , 2013, Inf. Sci..

[37]  Zhang-peng Tian,et al.  Multicriteria decision-making approach based on gray linguistic weighted Bonferroni mean operator , 2018, Int. Trans. Oper. Res..

[38]  Francisco Herrera,et al.  Hesitant Fuzzy Sets: State of the Art and Future Directions , 2014, Int. J. Intell. Syst..

[39]  Shu-Ping Wan,et al.  An intuitionistic fuzzy linear programming method for logistics outsourcing provider selection , 2015, Knowl. Based Syst..

[40]  Francisco Herrera,et al.  A fusion approach for managing multi-granularity linguistic term sets in decision making , 2000, Fuzzy Sets Syst..

[41]  Luis Martínez-López,et al.  An Overview on Fuzzy Modelling of Complex Linguistic Preferences in Decision Making , 2016, Int. J. Comput. Intell. Syst..

[42]  Zhang-peng Tian,et al.  Simplified Neutrosophic Linguistic Multi-criteria Group Decision-Making Approach to Green Product Development , 2017 .

[43]  Ronald R. Yager,et al.  The power average operator , 2001, IEEE Trans. Syst. Man Cybern. Part A.

[44]  Hong-yu Zhang,et al.  Multi-criteria decision-making based on hesitant fuzzy linguistic term sets: An outranking approach , 2015, Knowl. Based Syst..

[45]  Jun Ye,et al.  An extended TOPSIS method for multiple attribute group decision making based on single valued neutrosophic linguistic numbers , 2015, J. Intell. Fuzzy Syst..

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

[47]  Ronald R. Yager,et al.  Prioritized aggregation operators , 2008, Int. J. Approx. Reason..

[48]  Hai Wang,et al.  Extended hesitant fuzzy linguistic term sets and their aggregation in group decision making , 2015, Int. J. Comput. Intell. Syst..

[49]  Ali Emrouznejad,et al.  Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach , 2012, Expert Syst. Appl..

[50]  Jun Ye,et al.  Some aggregation operators of interval neutrosophic linguistic numbers for multiple attribute decision making , 2014, J. Intell. Fuzzy Syst..

[51]  Francisco Herrera,et al.  An overview on the 2-tuple linguistic model for computing with words in decision making: Extensions, applications and challenges , 2012, Inf. Sci..