Incomplete interval fuzzy preference relations for supplier selection in supply chain management

AbstractIn the analytical hierarchy process (AHP), it needs the decision maker to establish a pairwise comparison matrix requires n(n–1)/2 judgments for a level with n criteria (or alternatives). In some instances, the decision maker may have to deal with the problems in which only partial information and uncertain preference relation is available. Consequently, the decision maker may provide interval fuzzy preference relation with incomplete information. In this paper, we focus our attention on the investigation of incomplete interval fuzzy preference relation. We first extend a characterization to the interval fuzzy preference relation which is based on the additive transitivity property. Using the characterization, we propose a method to construct interval additive consistent fuzzy preference relations from a set of n–1 preference data. The study reveals that the proposed method can not only alleviate the comparisons, but also ensure interval preference relations with the additive consistent property. ...

[1]  Ying-Ming Wang,et al.  A goal programming method for obtaining interval weights from an interval comparison matrix , 2007, Eur. J. Oper. Res..

[2]  Jian-Bo Yang,et al.  A two-stage logarithmic goal programming method for generating weights from interval comparison matrices , 2005, Fuzzy Sets Syst..

[3]  Zenonas Turskis,et al.  Integrated Fuzzy Multiple Criteria Decision Making Model for Architect Selection , 2012 .

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

[5]  Yejun Xu,et al.  A note on group decision-making procedure based on incomplete reciprocal relations , 2011, Soft Comput..

[6]  Francisco Herrera,et al.  A consistency‐based procedure to estimate missing pairwise preference values , 2008, Int. J. Intell. Syst..

[7]  Ludmil Mikhailov,et al.  Fuzzy analytical approach to partnership selection in formation of virtual enterprises , 2002 .

[8]  J. Kacprzyk.  Group decision making with a fuzzy linguistic majority , 1986 .

[9]  Yejun Xu,et al.  Logarithmic least squares method to priority for group decision making with incomplete fuzzy preference relations , 2013 .

[10]  Yejun Xu,et al.  Least square completion and inconsistency repair methods for additively consistent fuzzy preference relations , 2012, Fuzzy Sets Syst..

[11]  Francisco Herrera,et al.  A Note on the Estimation of Missing Pairwise Preference Values: a Uninorm Consistency Based Method , 2008, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[12]  Francisco Herrera,et al.  Some issues on consistency of fuzzy preference relations , 2004, Eur. J. Oper. Res..

[13]  Sushil Kumar,et al.  Analytic hierarchy process: An overview of applications , 2006, Eur. J. Oper. Res..

[14]  Yejun Xu,et al.  Standard and mean deviation methods for linguistic group decision making and their applications , 2010, Expert Syst. Appl..

[15]  Moshe Kress,et al.  Approximate articulation of preference and priority derivation — a comment , 1991 .

[16]  Z. S. Xu,et al.  Goal programming models for obtaining the priority vector of incomplete fuzzy preference relation , 2004, Int. J. Approx. Reason..

[17]  Zeshui Xu,et al.  A Procedure for Decision Making Based on Incomplete Fuzzy Preference Relation , 2005, Fuzzy Optim. Decis. Mak..

[18]  James J. Buckley,et al.  Fuzzy hierarchical analysis: the Lambda-Max method , 2001, Fuzzy Sets Syst..

[19]  Yi Peng,et al.  Improved AHP-group decision making for investment strategy selection , 2012 .

[20]  Francisco Herrera,et al.  Group Decision-Making Model With Incomplete Fuzzy Preference Relations Based on Additive Consistency , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[21]  Yunliang Jiang.  An approach to group decision making based on interval fuzzy preference relations , 2007 .

[22]  Francisco Herrera,et al.  Managing non-homogeneous information in group decision making , 2005, Eur. J. Oper. Res..

[23]  Kwai-Sang Chin,et al.  An eigenvector method for generating normalized interval and fuzzy weights , 2006, Appl. Math. Comput..

[24]  Ami Arbel,et al.  Approximate articulation of preference and priority derivation , 1989 .

[25]  Yejun Xu.  Note on "The induced continuous ordered weighted geometric operators and their application in group decision making" , 2010, Comput. Ind. Eng..

[26]  T. Tanino.  Fuzzy preference orderings in group decision making , 1984 .

[27]  Francisco Herrera,et al.  A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations , 2007, IEEE Transactions on Fuzzy Systems.

[28]  M. Bohanec,et al.  The Analytic Hierarchy Process , 2004 .

[29]  Yejun Xu,et al.  Normalizing rank aggregation method for priority of a fuzzy preference relation and its effectiveness , 2009, Int. J. Approx. Reason..

[30]  Karel Skokan.  Technological and Economic Development of Economy , 2011 .

[31]  Gaļina Merkurjeva,et al.  Multi-Objective Stochastic Simulation-Based Optimisation Applied to Supply Chain Planning , 2012 .

[32]  WangYing-Ming,et al.  A two-stage logarithmic goal programming method for generating weights from interval comparison matrices , 2005 .

[33]  Ying-Ming Wang,et al.  On lexicographic goal programming method for generating weights from inconsistent interval comparison matrices , 2006, Appl. Math. Comput..

[34]  Tien-Chin Wang,et al.  Applying consistent fuzzy preference relations to partnership selection , 2007 .

[35]  Yueh-Hsiang Chen,et al.  Applying fuzzy linguistic preference relations to the improvement of consistency of fuzzy AHP , 2008, Inf. Sci..

[36]  T. Saaty.  Analytic Hierarchy Process , 2005 .

[37]  Luis G. Vargas,et al.  Uncertainty and rank order in the analytic hierarchy process , 1987 .

[38]  Zeshui Xu,et al.  On Compatibility of Interval Fuzzy Preference Relations , 2004, Fuzzy Optim. Decis. Mak..

[39]  M. P. Biswal,et al.  Preference programming and inconsistent interval judgments , 1997 .

[40]  Michele Fedrizzi,et al.  Incomplete pairwise comparison and consistency optimization , 2007, Eur. J. Oper. Res..