Application of quantum-like Bayesian network and belief entropy for interference effect in multi-attribute decision making problem

2021 ◽  
Vol 157 ◽  
pp. 107307
Author(s):  
Lulu She ◽  
Shilian Han ◽  
Xinwang Liu
Keyword(s):  
Decision Making ◽  
Bayesian Network ◽  
Interference Effect ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
Belief Entropy

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 Possibility Neutrosophic Cubic Sets and Their Application to Multiple Attribute Decision Making

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 269 ◽  
Author(s):  
Huiling Xue ◽  
Xiaotong Yang ◽  
Chunfang Chen
Keyword(s):  
Decision Making ◽  
Binary Operation ◽  
Score Function ◽  
Multiple Attribute Decision Making ◽  
Membership Degree ◽  
Neutrosophic Sets ◽  
Important Indicator ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making

The neutrosophic cubic sets are an extension of the cubic sets to the neutrosophic sets. It contains three variables, which respectively represent the membership degree, non-membership degree and uncertainty of the element to the set. The score function is an important indicator in the multi-attribute decision-making problem. In this paper, we consider the possibility that an element belongs to a set and put forward the concept of possibility neutrosophic cubic sets. On this basis, we introduce some related concepts and give the binary operation of possibility neutrosophic cubic sets and use specific examples to supplement the corresponding definition. Meanwhile, a decision-making method based on the score function of possibility neutrosophic cubic sets is proposed and a numerical example is given to illustrate the effectiveness of the proposed method.

A Service Selection Algorithm Based on Heterogeneous QoS Model and Synthetic Weights

2015 ◽  
Vol 734 ◽  
pp. 459-462 ◽  
Author(s):  
Sen Zeng ◽  
Guo Qi Ni ◽  
Miao Miao Fan ◽  
Lin Zhang ◽  
Yuan Hua He
Keyword(s):  
Decision Making ◽  
Service Selection ◽  
Selection Problem ◽  
Final Decision ◽  
Selection Algorithm ◽  
Decision Making Problem ◽  
Different Types ◽  
Traditional Service ◽  
Multi Attribute Decision Making

Quality of Service (QoS) aware-based service selection problem is a multi-attribute decision making problem. In order to solve service selection problem with QoS indicators describe by different types of data, a service selection algorithm based on heterogeneous QoS model and synthetic weight (SSAoHS) is proposed. SSAoHS introduces real number, interval number and linguistic data to describe different QoS attributes, considers the subjective and objective weights wholly, and makes the final decision referring to the expectation and variance of QoS attributes after computing the synthetic scores. SSAoHS expands the traditional service selection and it is efficient and effective.

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