A method for intuitionistic fuzzy multi-attribute decision making with incomplete attribute weight information

Abstract

A new method for solving intuitionistic fuzzy multi-attribute decision making problem is proposed, in which the information of attribute weights is incompletely known. Considering much information about hesitancy and vagueness inherited to intuitionistic fuzzy sets, a new class of distance for describing the deviation degrees between intuitionistic fuzzy sets is introduced. Furthermore, the measure of similarity degree for each alternative to ideal point is calculated by using the new proposed fuzzy distance. A model of TOPSIS is designed with the introduction of the particular closeness coefficient composed of similarity degrees for alternative ranking. Finally, a numerical example is given to show feasibility and effectiveness of the developed method. © 2005 - 2013 JATIT & LLS.