Soft computing based on new interval-valued fuzzy modified multi-criteria decision-making method

In this paper, a new interval-valued fuzzy modified TOPSIS (IVFM-TOPSIS) method is proposed that can reflect both subjective judgment and objective information in real life situations. This proposed method is based on concepts of the positive ideal and negative ideal solutions for solving multi-criteria decision-making (MCDM) problems in a fuzzy environment. The performance rating values and weights of criteria are linguistic variables expressed as triangular interval-valued fuzzy numbers. Furthermore, we appraise the performance of alternatives against both subjective and objective criteria with multi-judges for decision-making problems. Finally, for the purpose of proving the validity of the proposed method a numerical example is presented for a robot selection problem.

[1]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[2]  M. Gorzałczany A method for inference in approximate reasoning based on interval-valued fuzzy sets , 1987 .

[3]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[4]  Habib Chabchoub,et al.  PROMETHEE-MD-2T method for project selection , 2009, Eur. J. Oper. Res..

[5]  Gwo-Hshiung Tzeng,et al.  Extended VIKOR method in comparison with outranking methods , 2007, Eur. J. Oper. Res..

[6]  Raimo P. Hämäläinen,et al.  Decision Support by Interval SMART/SWING - Incorporating Imprecision in the SMART and SWING Methods , 2005, Decis. Sci..

[7]  Shyi-Ming Chen,et al.  Fuzzy risk analysis based on interval-valued fuzzy numbers , 2009, Expert Syst. Appl..

[8]  Jerry M. Mendel,et al.  Operations on type-2 fuzzy sets , 2001, Fuzzy Sets Syst..

[9]  Ming-Shin Kuo,et al.  A novel interval-valued fuzzy MCDM method for improving airlines’ service quality in Chinese cross-strait airlines , 2011 .

[10]  Ronald R. Yager,et al.  Level sets and the extension principle for interval valued fuzzy sets and its application to uncertainty measures , 2008, Inf. Sci..

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

[12]  I. Turksen Interval-valued fuzzy sets and “compensatory AND” , 1992 .

[13]  Evangelos Triantaphyllou,et al.  Multi-criteria Decision Making Methods: A Comparative Study , 2000 .

[14]  I. Burhan Türksen,et al.  Interval valued strict preference with Zadeh triples , 1996, Fuzzy Sets Syst..

[15]  Ming-Miin Yu,et al.  Decision Making Based On Statistical Data, Signed Distance And Compositional Rule Of Inference , 2004, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

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

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

[18]  André Bigand,et al.  Fuzzy filter based on interval-valued fuzzy sets for image filtering , 2010, Fuzzy Sets Syst..

[19]  Edmundas Kazimieras Zavadskas,et al.  Multicriteria selection of project managers by applying grey criteria , 2008 .

[20]  Mao-Jiun J. Wang,et al.  A fuzzy multi-criteria decision-making approach for robot selection , 1993 .

[21]  P. Sevastianov,et al.  MCDM in a fuzzy setting: Investment projects assessment application , 2006 .

[22]  R. Tavakkoli-Moghaddam,et al.  A multi-stage decision-making process for multiple attributes analysis under an interval-valued fuzzy environment , 2013 .

[23]  Salvatore Greco,et al.  Rough set approach to multiple criteria classification with imprecise evaluations and assignments , 2009, Eur. J. Oper. Res..

[24]  Xiaoping Li,et al.  The applications of interval-valued fuzzy numbers and interval-distribution numbers , 1998, Fuzzy Sets Syst..

[25]  Dug Hun Hong,et al.  Some algebraic properties and a distance measure for interval-valued fuzzy numbers , 2002, Inf. Sci..

[26]  Reza Tavakkoli-Moghaddam,et al.  A novel two-phase group decision making approach for construction project selection in a fuzzy environment , 2012 .

[27]  Behnam Vahdani,et al.  Extension of the ELECTRE method based on interval-valued fuzzy sets , 2011, Soft Comput..

[28]  Humberto Bustince,et al.  Mathematical analysis of interval-valued fuzzy relations: Application to approximate reasoning , 2000, Fuzzy Sets Syst..

[29]  Reza Tavakkoli-Moghaddam,et al.  A Fuzzy Stochastic Multi-Attribute Group Decision-Making Approach for Selection Problems , 2011, Group Decision and Negotiation.

[30]  Chris Cornelis,et al.  Advances and challenges in interval-valued fuzzy logic , 2006, Fuzzy Sets Syst..

[31]  Miin-Shen Yang,et al.  Interval-valued fuzzy relation-based clustering with its application to performance evaluation , 2009, Comput. Math. Appl..