Method for Fuzzy Interval Numbers Multi-attribute Decision Making with Preference Information

2008 ◽  
Author(s):  
Deng Jiangao ◽  
Yanbing Gong ◽  
Jiguo Zhang
Keyword(s):  
Decision Making ◽  
Interval Numbers ◽  
Preference Information ◽  
Multi Attribute Decision Making ◽  
Fuzzy Interval

Projection Method for Material Selection Problem with Interval Numbers

2014 ◽  
Vol 1022 ◽  
pp. 14-17 ◽  
Author(s):  
Lian Wu Yang
Keyword(s):  
Decision Making ◽  
Projection Method ◽  
Coefficient Of Variation ◽  
Material Selection ◽  
Influence Factors ◽  
Selection Problem ◽  
Variation Method ◽  
Interval Numbers ◽  
Decision Method ◽  
Multi Attribute Decision Making

Material selection problem is important for the product design, and contains many influence factors. Thus it is actually a multi-attribute decision making (MADM) problems. The aim of this paper is to propose a new decision method based on the projection method for the material selection problem, in which attribute values expressed with interval numbers. An objective determining weights method is proposed according to coefficient of variation method. A practical example is used to illustrate the effectiveness and practicability of the proposed method.

PROJECTION METHOD FOR UNCERTAIN MULTI-ATTRIBUTE DECISION MAKING WITH PREFERENCE INFORMATION ON ALTERNATIVES

2004 ◽  
Vol 03 (03) ◽  
pp. 429-434 ◽  
Author(s):  
ZESHUI XU ◽  
QINGLI DA
Keyword(s):  
Decision Making ◽  
Projection Method ◽  
Multiple Attribute Decision Making ◽  
Projection Model ◽  
Preference Information ◽  
Objective Information ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making

In this paper, we study the uncertain multiple attribute decision making problems with preference information on alternatives (UMADM-PIA, for short), in which the information on attribute weights is not precisely known, but value ranges can be obtained. A projection method is proposed for the UMADM-PIA. To reflect the decision maker's preference information, a projection model is established to determine the weights of attributes, and then to select the most desirable alternative(s). The method can reflect both the objective information and the decision maker's subjective preferences, and can also be performed on computer easily. Finally, an illustrative example is given to verify the proposed method and to demonstrate its feasibility and practicality.

scholarly journals An Extended VIKOR Method Based on q-Rung Orthopair Shadowed Set and Its Application to Multi-Attribute Decision Making

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1508
Author(s):  
Huidong Wang ◽  
Yao Zhang ◽  
Jinli Yao
Keyword(s):  
Decision Making ◽  
Normal Distribution ◽  
Distance Measures ◽  
Basic Operation ◽  
Interval Numbers ◽  
Location Selection ◽  
Operation Rules ◽  
Shadowed Set ◽  
Multi Attribute Decision Making ◽  
Shadowed Sets

In the multi-attribute decision making (MADM) process, the attribute values are sometimes provided by experts or the public in the form of words. To model the linguistic evaluation more accurately, this paper proposes the q-rung orthopair shadowed set (q-ROSS) to represent attribute values and extends the VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) method to solve MADM problems in the q-ROSS context. First, we propose the q-ROSS to express evaluation information. Some basic operation rules and distance measures are investigated accordingly. When the amount of data is large, the left and right endpoints of the collected interval numbers will obey symmetric normal distribution. Secondly, based on the normal distribution assumption, the collected data intervals are mapped to shadowed sets through a data processing approach. Furthermore, we extend the VIKOR model to tackle the MADM problem where the evaluation values are expressed by q-rung orthopair shadowed numbers. A location selection problem verifies the practicability of our method, and the effectiveness and superiority of the presented approach are reflected through comparative analysis.

Study on Filter Algorithm of QoS-Based Fuzzy Multi-Attribute Web Service Composition

2012 ◽  
Vol 182-183 ◽  
pp. 2131-2135
Author(s):  
Xiang Rong Fang
Keyword(s):  
Decision Making ◽  
Web Service ◽  
Information Matrix ◽  
Service Selection ◽  
Fuzzy Decision Making ◽  
Interval Numbers ◽  
Functional Attributes ◽  
Web Service Selection ◽  
Multi Attribute Decision Making ◽  
Definition Of

In this paper, an in-depth research has been done on the physical meaning and value features of the QoS attribute values under the definition of the functional attributes and non-functional attributes of Web services, giving the computation formulae and matching method expressing QoS composition as interval numbers, providing a more comprehensive and objective information matrix for fuzzy multi-attribute decision making. For multi-attributes fuzzy decision-making matrix with weight information known and the preference information of composition solution given in the form of interval numbers, calculating the overall attribute values, and sorting solutions by using the formula of probability degree, a QoS-driven multi-level composition Web Service selection algorithm is proposed, and simulation runs indicate the feasibility and effectiveness of the algorithm.

Entropy method of determining the attribute weights of interval numbers based on relative superiority

2021 ◽  
pp. 1-8
Author(s):  
Lin Li ◽  
Tiejun Ci ◽  
Xiaoyu Yang ◽  
Heng Du ◽  
Haocan Ma ◽  
...  
Keyword(s):  
Decision Making ◽  
Basic Principle ◽  
Multiple Attribute Decision Making ◽  
Entropy Method ◽  
Interval Numbers ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making ◽  
Judgment Matrix ◽  
Train Of Thought

In view of the multi-attribute decision making problems which the attribute values are in the forms of interval numbers, the paper presents an entropy method to obtain the attribute weights using the relative superiority concept. Firstly, the concept of this kind of problem is explained; Then in the light of the basic principle of the traditional entropy value method and train of thought, it given the calculation steps of weights using the relative superiority about the attribute value is interval number multiple attribute decision making problems. Its core is that relative superiority judgment matrix is obtained by comparing with two sets of interval numbers under the same indicator, which the group of interval numbers is equivalently mapped to the exact value form with the merits of relationship, then the weights of each indicator are calculated. Finally, the method is illustrated by giving an example.

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