Research on Multi-Attribute Decision Making Using Grey Relation Analysis, Information Axiom and Fuzzy Preferences

2008 ◽  
Vol 44-46 ◽  
pp. 587-594 ◽  
Author(s):  
Xian Fu Cheng
Keyword(s):  
Decision Making ◽  
Information Content ◽  
Data Series ◽  
Grey Relation Analysis ◽  
Fuzzy Preferences ◽  
Information Axiom ◽  
Multi Attribute Decision Making ◽  
Relation Analysis ◽  
Grey Relation ◽  
The Ideal

The grey relation analysis is a kind of quantitative analysis method based on factors compared. The information axiom of axiomatic design provides a mean of evaluation by comparing the information content of several alternatives, based on which a new method for multi-attribute decision making is proposed. First, according to decision matrix of all decision making criteria, the ideal alternative composed of the best reference data series among all alternatives is constructed. Then the information content is used to evaluate the relation grade between an individual alternative and the ideal alternative. The fuzzy preferences are utilized to determine the weight of each criterion. The total information content of every alternative is calculated, and arrayed in order, so the optimal alternative can be selected. For requirements of evaluation, the calculation formula of information content is amended. Finally, an example is given to illustrate the effectiveness and feasibility of the proposed method.

Material Selection Using TOPSIS Combined with Grey Relation Analysis

2014 ◽  
Vol 540 ◽  
pp. 476-479 ◽  
Author(s):  
Xue Jun Xie
Keyword(s):  
Material Selection ◽  
Selection Problem ◽  
Grey Relation Analysis ◽  
Real Material ◽  
Selection Decisions ◽  
Multi Attribute Decision Making ◽  
Relation Analysis ◽  
Optimal Material ◽  
Grey Relation ◽  
Selection Of

The selection of an optimal material is an important aspect of design for mechanical, electrical, thermal, chemical or other application. Material selection problem is a multi-attribute decision making (MADM) problem, which has several evaluation attributes. The selection decisions are complex, as material selection is more challenging today. This paper proposes a new MADM method for material selection problem. Combining the TOPSIS with grey relation analysis, the method proposed a comprehensive value to evaluate and select the best alternative. A real material selection case is used to demonstrate that the proposed method is effectiveness and feasibility.

Multi-Attribute Decision Making Method Based-On Information Axiom with Incomplete Information for Functional Requirements

2010 ◽  
Vol 37-38 ◽  
pp. 697-701
Author(s):  
Xian Fu Cheng
Keyword(s):  
Decision Making ◽  
Incomplete Information ◽  
Information Content ◽  
New Method ◽  
Final Decision ◽  
Functional Requirements ◽  
Acceptable Range ◽  
Information Axiom ◽  
Multi Attribute Decision Making ◽  
Total Information Content

For multi-attribute decision making problems including quantitative and fuzzy criteria, a new method with incomplete information for functional requirements based-on information axiom was proposed. When several alternatives satisfy the FRs, the satisfactory degree of users are taken into account in the process of multi-attribute decision making. When the design range of the criterion is unknown, the acceptable range is defined and considered as the design range. The definition and formulation of information content with incomplete information for multi-attribute decision making was developed. All alternatives can be ranked by the total information content, and a final decision was made for the best alternative. Finally, an example on punching machines’ evaluation and selection was used to illustrate the proposed method.

Decision Making on Engineering Materials Based on Relative Grey Relation Analysis

2013 ◽  
Vol 753-755 ◽  
pp. 1620-1624
Author(s):  
Dong Jing Wang ◽  
An Hua Peng
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Maximum Deviation ◽  
Grey Relation Analysis ◽  
Relational Analysis ◽  
Relation Analysis ◽  
Engineering Materials ◽  
Grey Relational ◽  
The Relationship ◽  
Grey Relation

The quality and cost of a product rely heavily on selecting suitable engineering materials, and therefore the ability to select the most appropriate material for a given application is the fundamental challenges faced by the design engineer. The general grey relational analysis (GRA) has three weaknesses: (1) weight determination depends only on expert judgments; (2) the qualitative indexes are only simply quantified with exact number; and (3) the general GRA only takes into account the relationship between the imaginarily best material and the candidate materials. The GRA is extended to RGRA, weights are determined by combining subjective and objective weights based on maximum deviation, and the qualitative indexes are fuzzily quantified through trapezoidal fuzzy number (TFN). The illustrative example shows that the presented method enables decision making results to be more reasonable and trustworthy.

Grey Relation Analysis Method for Material Selection Problem with Interval Numbers

2014 ◽  
Vol 1014 ◽  
pp. 492-496 ◽  
Author(s):  
Lian Wu Yang
Keyword(s):  
Decision Making ◽  
Material Selection ◽  
Selection Problem ◽  
Variation Method ◽  
Analysis Method ◽  
Grey Relation Analysis ◽  
Interval Numbers ◽  
Attribute Weights ◽  
Relation Analysis ◽  
Grey Relation

Material selection is an important step in the product design process. Material selection problem contains many influence factors, and thus it is actually a multi-attribute decision making problem. In some situations, measure values cannot or unsuitable to be depicted by crisp numbers. Interval number is a suitable selection in these situations, and for the material selection problem with interval numbers, a new decision making method is developed based on grey relation analysis method. The attribute weights will be determined by the coefficient of variation method. Finally, a practical example is used to illustrate the effectiveness and feasibility of the proposed method.

Fuzzy grey relation analysis on torque influence factors of alternating current electrodyna-mometer

2013 ◽  
Vol 26 (8) ◽  
pp. 693-698 ◽  
Author(s):  
Zhigang Zhang ◽  
Guixiang Zhang ◽  
Teng Liu ◽  
Cheng Qian ◽  
Yuanwang Deng
Keyword(s):  
Influence Factors ◽  
Alternating Current ◽  
Grey Relation Analysis ◽  
Relation Analysis ◽  
Grey Relation
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