The TOPSIS Method of Multiple Attribute Decision Making Problem with Triangular-fuzzy-valued Weight

2008 ◽  
Author(s):  
Yuan-guang Fu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Topsis Method ◽  
Multiple Attribute ◽  
Decision Making Problem

An Improved Method for Solving Multi-Attribute Problem in Transportation Mode Decision Making Process

2014 ◽  
Vol 1030-1032 ◽  
pp. 1961-1965
Author(s):  
Bao Shan Lin ◽  
Yan Bin Fan
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Entropy Method ◽  
Topsis Method ◽  
Transportation Mode ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
Time Price ◽  
Transportation Activity

In logistics activities, the choice of the transportation mode involves time, price, safety, and many other factors, it is a typical multi-attribute decision making problem. Traditionally, we usually adopt a certain decision-making method to solve such problems, but the resulting solution is often difficult to achieve our desired results. This article tries to combine AHP, information entropy method and the TOPSIS method to solve the multiple-attribute decision making problems in the process of transportation activity, and finally a case is given.

TOPSIS Method for Multiple Attribute Decision Making Problem in Intuitionistic Fuzzy Setting

2013 ◽  
Vol 427-429 ◽  
pp. 1888-1891
Author(s):  
Yuan Yuan He ◽  
Zai Wu Gong
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Fuzzy Information ◽  
Topsis Method ◽  
Intuitionistic Fuzzy Numbers ◽  
Attribute Weights ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Fuzzy Setting

This paper is concerned with a TOPSIS method for fuzzy multiple attribute decision making, in which the information about attribute weights is completely known and the attribute values take form of intuitionistic fuzzy numbers. A class of distance for describing the deviation degrees between intuitionistic fuzzy sets is used to measure difference between two alternatives. A model of TOPSIS is designed with the introduction of the particular closeness coefficient composed of similarity degrees. Then, we apply the TOPSIS method to aggregate the fuzzy information corresponding to each alternative, and rank the alternatives according to their closeness coefficients. Finally, a numerical example is given to show the feasibility and effectiveness of the method.

scholarly journals A Method Based on Intuitionistic Fuzzy Dependent Aggregation Operators for Supplier Selection

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Fen Wang ◽  
Shouzhen Zeng ◽  
Chonghui Zhang
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operators ◽  
Intuitionistic Fuzzy ◽  
Strategic Factor ◽  
Multiple Attribute ◽  
Fuzzy Aggregation ◽  
Decision Making Problem

Recently, resolving the decision making problem of evaluation and ranking the potential suppliers have become as a key strategic factor for business firms. In this paper, two new intuitionistic fuzzy aggregation operators are developed: dependent intuitionistic fuzzy ordered weighed averaging (DIFOWA) operator and dependent intuitionistic fuzzy hybrid weighed aggregation (DIFHWA) operator. Some of their main properties are studied. A method based on the DIFHWA operator for intuitionistic fuzzy multiple attribute decision making is presented. Finally, an illustrative example concerning supplier selection is given.

Sign in / Sign up

Export Citation Format

Share Document