New intuitionistic fuzzy approach with multi-objective optimisation on the basis of ratio analysis method

Application of MCDM methods in different fields of knowledge is increasing and new techniques are invented to help decision experts achieving optimised solution and getting reliable and facilitated route to final decision. Multi-objective optimisation on the basis of ratio analysis (MOORA) is a recent and novel tool invented and employed in many scientific projects. In other side, in every decision environment, there are massive information and undetermined situations which affect decision process and evidently its outcomes. Therefore, to improve decision preciseness and to overcome vagueness in uncertain environments, fuzzy theory and newly intuitionistic fuzzy approach try to get more reliable solutions. In this paper, a new version of intuitionistic fuzzy MOORA technique is proposed with triangular fuzzy numbers in a group decision making situation. Ultimately, a case of project selection problem is supposed to validate the applicability of the proposed approach.

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

[2]  Kenneth J. Arrow,et al.  General Economic Equilibrium: Purpose, Analytic Techniques, Collective Choice , 1972 .

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

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

[5]  Etienne E. Kerre,et al.  Reasonable properties for the ordering of fuzzy quantities (II) , 2001, Fuzzy Sets Syst..

[6]  Ronald R. Yager,et al.  Intuitionistic fuzzy interpretations of multi-criteria multi-person and multi-measurement tool decision making , 2005, Int. J. Syst. Sci..

[7]  Ching-Hsue Cheng,et al.  Using intuitionistic fuzzy sets for fault-tree analysis on printed circuit board assembly , 2006, Microelectron. Reliab..

[8]  Edmundas Kazimieras Zavadskas,et al.  The MOORA method and its application to privatization in a transition economy , 2006 .

[9]  Zhifeng Chen,et al.  Linguistic group decision-making: opinion aggregation and measures of consensus , 2006, Fuzzy Optim. Decis. Mak..

[10]  Zeshui Xu,et al.  Intuitionistic Fuzzy Aggregation Operators , 2007, IEEE Transactions on Fuzzy Systems.

[11]  Deng-Feng Li,et al.  A note on "using intuitionistic fuzzy sets for fault-tree analysis on printed circuit board assembly" , 2008, Microelectron. Reliab..

[12]  A. K. Ray,et al.  A new measure using intuitionistic fuzzy set theory and its application to edge detection , 2008, Appl. Soft Comput..

[13]  E. Zavadskas,et al.  Multi‐objective contractor's ranking by applying the Moora method , 2008 .

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

[15]  Morteza Pakdin Amiri,et al.  Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods , 2010, Expert Syst. Appl..

[16]  E. Zavadskas,et al.  Project management by multimoora as an instrument for transition economies , 2010 .

[17]  Zeshui Xu,et al.  A method based on distance measure for interval-valued intuitionistic fuzzy group decision making , 2010, Inf. Sci..

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

[19]  W. Brauers,et al.  Regional development in Lithuania considering multiple objectives by the MOORA method , 2010 .

[20]  Renato A. Krohling,et al.  Fuzzy TOPSIS for group decision making: A case study for accidents with oil spill in the sea , 2011, Expert Syst. Appl..

[21]  Shankar Chakraborty,et al.  Applications of the MOORA method for decision making in manufacturing environment , 2011 .

[22]  Kavita Devi,et al.  Extension of VIKOR method in intuitionistic fuzzy environment for robot selection , 2011, Expert Syst. Appl..

[23]  Shyi-Ming Chen,et al.  Multiattribute decision making based on interval-valued intuitionistic fuzzy values , 2012, Expert Syst. Appl..

[24]  Alvydas Balezentis,et al.  Personnel selection based on computing with words and fuzzy MULTIMOORA , 2012, Expert Syst. Appl..

[25]  S. Chakraborty,et al.  Application of multi-objective optimization on the basis of ratio analysis (MOORA) method for materials selection , 2012 .

[26]  Morteza Yazdani,et al.  A state-of the-art survey of TOPSIS applications , 2012, Expert Syst. Appl..

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

[28]  Dragisa Stanujkic,et al.  Extension of Ratio System Part of MOORA Method for Solving Decision-Making Problems with Interval Data , 2012, Informatica.

[29]  Wieslaw A. Dudek,et al.  Intuitionistic fuzzy hypergraphs with applications , 2013, Inf. Sci..

[30]  S. M. Mousavi,et al.  A new design of the elimination and choice translating reality method for multi-criteria group decision-making in an intuitionistic fuzzy environment , 2013 .

[31]  Shouzhen Zeng,et al.  Group multi-criteria decision making based upon interval-valued fuzzy numbers: An extension of the MULTIMOORA method , 2013, Expert Syst. Appl..

[32]  Davide Aloini,et al.  A peer IF-TOPSIS based decision support system for packaging machine selection , 2014, Expert Syst. Appl..

[33]  Jiuying Dong,et al.  A possibility degree method for interval-valued intuitionistic fuzzy multi-attribute group decision making , 2014, J. Comput. Syst. Sci..

[34]  K. Wong,et al.  Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process , 2015 .

[35]  Dariush Khezrimotlagh,et al.  An integrated model for green supplier selection under fuzzy environment: application of data envelopment analysis and genetic programming approach , 2015, Neural Computing and Applications.

[36]  Morteza Yazdani,et al.  A comparative study on material selection of microelectromechanical systems electrostatic actuators using Ashby, VIKOR and TOPSIS , 2015 .