A DS–AHP approach for multi-attribute decision making problem with incomplete information

2008 ◽  
Vol 34 (3) ◽  
pp. 2221-2227 ◽  
Author(s):  
Zhongsheng Hua ◽  
Bengang Gong ◽  
Xiaoyan Xu
Keyword(s):  
Decision Making ◽  
Incomplete Information ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making

scholarly journals A Multi-Attribute Decision-Making Algorithm Using Q-Rung Orthopair Power Bonferroni Mean Operator and Its Application

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1240 ◽  
Author(s):  
Ping He ◽  
Zaoli Yang ◽  
Bowen Hou
Keyword(s):  
Decision Making ◽  
Influence Factors ◽  
Uncertain Information ◽  
Fuzzy Information ◽  
Bonferroni Mean ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
New Type ◽  
Multiple Variables ◽  
Internal Relationship

The process of decision-making is subject to various influence factors and environmental uncertainties, which makes decision become a very complex task. As a new type of decision processing tool, the q-rung orthopair fuzzy sets can effectively deal with complex uncertain information arising in the decision process. To this end, this study proposes a new multi-attribute decision-making algorithm based on the power Bonferroni mean operator in the context of q-rung orthopair fuzzy information. In this method, in view of multi-attribute decision-making problem of internal relationship between multiple variables and extreme evaluation value, the Bonferroni mean operator is combined with power average operator. Then, the integrated operator is introduced into the q-rung orthopair fuzzy set to develop a new q-rung orthopair power Bonferroni mean operator, and some relevant properties of this new operator are discussed. Secondly, a multi-attribute decision-making method is established based on this proposed operator. Finally, the feasibility and superiority of our method are testified via a numerical example of investment partner selection in the tourism market.

scholarly journals Multi-Attribute Decision Making Based on Attribute Importance Degree and Case-Based Reasoning

2013 ◽  
Vol 13 (Special-Issue) ◽  
pp. 62-74 ◽  
Author(s):  
Zhong Wu ◽  
Ruixia Yan
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Rough Set Theory ◽  
Importance Measure ◽  
Case Based Reasoning ◽  
Relative Importance ◽  
Attribute Importance ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
Case Based

Abstract To tackle a multi-attribute decision making problem, rough set and casebased reasoning are often combined. However, the reduction in a rough set is always complex. In this paper we provide a new relative importance measure about the unitary attributes values by ranking the relative importance of the attributes in the rough set theory. A new rough set model based on ranking the relative importance of the attributes is built and its properties are studied. Then unitary attributes values are utilized to compute the similarity of rules in case-based reasoning, for there might be incompletely match or miss values. A new multiattribute decision making based on case-based reasoning and a rough set based on the ranking relative importance of the attributes is constructed, which obtains rules, avoiding reduction and rule extraction.

scholarly journals A Method of Determining Multi-Attribute Weights Based on Single-Valued Neutrosophic Numbers and Its Application in TODIM

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 506 ◽  
Author(s):  
Dongsheng Xu ◽  
Yanran Hong ◽  
Kaili Xiang
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Entropy Weight ◽  
Attribute Weights ◽  
Attribute Weight ◽  
Decision Making Problem ◽  
Entropy Weight Method ◽  
Todim Method ◽  
Multi Attribute Decision Making ◽  
Weight Method

In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this proposed method.

scholarly journals Incomplete Fuzzy Soft Sets and Their Application to Decision-Making

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 535 ◽  
Author(s):  
Lu Wang ◽  
Keyun Qin
Keyword(s):  
Decision Making ◽  
Weight Function ◽  
Incomplete Information ◽  
Soft Set ◽  
Fuzzy Soft Set ◽  
Precise Description ◽  
Soft Sets ◽  
Weighted Function ◽  
Decision Making Problem ◽  
Fuzzy Soft Sets

The research of incomplete fuzzy soft sets is of paramount importance in fuzzy soft sets, where the combination of incomplete fuzzy soft set and decision-making problem is of great significance. Incomplete information in fuzzy soft sets leads to more uncertainty and ambiguity in decision-making. The focus of this paper to propose an algorithm of fuzzy soft set based decision-making problems under incomplete information. On the basis of the weighted function, we introduce the notions of weighted incomplete soft sets and weighted incomplete fuzzy soft sets, and show an approach to weighted incomplete fuzzy soft sets for dealing with decision-making. Considering the missing weight function, the concept of incomplete weighted fuzzy soft sets is presented. Meanwhile, we apply the incomplete weighted fuzzy soft sets to solve the decision-making problem. As modal-style operators for fuzzy soft sets have a precise description of attributes possessed by objects, we apply modal-style operator for incomplete fuzzy soft set to deal with decision-making and propose a new algorithm to make it more accurate and simple.

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