Decision-making Methods with Three-parameter Interval Grey Number

2009 ◽  
Vol 29 (1) ◽  
pp. 124-130 ◽  
Author(s):  
Dang LUO
Keyword(s):  
Decision Making ◽  
Parameter Interval ◽  
Grey Number

Grey relational decision making model of three-parameter interval grey number based on AHP and DEA

2019 ◽  
Vol 10 (1) ◽  
pp. 25-37
Author(s):  
Bingjun Li ◽  
Xiaoxiao Zhu
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Agriculture Industry ◽  
Parameter Interval ◽  
Grey Number ◽  
Index Weight ◽  
Decision Making Model ◽  
Grey Relational ◽  
Grey Relation

Purpose The purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA), based on the previous study of grey relational decision-making model, and it considers the advantages of the decision-making schemes and the subjective preferences of decision makers. Design/methodology/approach First of all, through AHP, the preference of each index is analyzed and the index weight is determined. Second, the DEA model is adopted to obtain the index weight from the perspective of the most beneficial to each scheme and objectively reflect the advantages of different schemes. Then, assign the comprehensive weights to each index of the grey relational decision-making model of three-parameter interval grey number, and calculate the grey relation degree of each scheme to rank the schemes. Findings The effectiveness of the model is proved by an example of carrier aircraft selection. Practical implications The applicability of this model is analyzed by taking carrier aircraft selection as an example. In fact, this model can also be widely used in agriculture, industry, economy, society and other fields. Originality/value In this paper, the combination of AHP and DEA is used to determine the index weight. Based on which, the grey relation degree under the three-parameter interval grey number is calculated. It intended the application space of the grey relational decision-making model.

Multi-attribute grey target decision method with three-parameter interval grey number

2016 ◽  
Vol 6 (2) ◽  
pp. 270-280 ◽  
Author(s):  
Ye Li ◽  
Shanli Zhu ◽  
San-dang Guo
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Ranking Method ◽  
Content Type ◽  
Uncertain Environment ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number ◽  
Bull's Eye

Purpose – The purpose of this paper is to propose the grey target decision method based on three-parameter interval grey number for dealing with multi-attribute decision-making problems under uncertain environment. Design/methodology/approach – First, the kernel and ranking method of three-parameter interval grey number are defined, which is the basis of determining the positive and negative bull’s-eye. Next, a new distance measure of three-parameter interval grey number is defined in view of the importance of the “center of gravity” point. Furthermore, a new comprehensive bull’s-eye distance is proposed based on the kernel which integrates the distance between different attributes to the positive and negative bull’s-eye. Then attribute weights are obtained by comprehensive bull’s-eye distance minimum and grey entropy maximization. Findings – The paper provides a grey target decision method based on three-parameter interval grey number and example analysis shows that the method proposed in this paper is more reasonable and effective. Research limitations/implications – If we have a better understanding of the distribution characteristics of three-parameter interval grey number, it is possible to have a more reasonable measure of the distance of three-parameter interval grey number. Practical implications – The paper provides a grey target decision method, which can help decision maker deal with multi-attribute decision-making problems under uncertain environment. Originality/value – This paper proposed the kernel and ranking method of three-parameter interval grey number, and defined a new distance measure of three-parameter interval grey number and proposed a new comprehensive bull’s-eye distance, Furthermore, this paper structured a grey target decision method based on three-parameter interval grey number.

Dynamic multi-attribute decision-making method with three-parameter interval grey number based on the prospect theory

2018 ◽  
Vol 8 (4) ◽  
pp. 424-435 ◽  
Author(s):  
Ye Li ◽  
Dongxing Zhang
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Value Function ◽  
Reference Points ◽  
Content Type ◽  
Time Points ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number

Purpose The purpose of this paper is to propose a dynamic multi-attribute decision-making method based on the prospect theory for dealing with the dynamic multi-attribute decision-making problem with three-parameter interval grey number. Design/methodology/approach First, the kernel and comparison rule of three-parameter interval grey numbers are defined, which are the basis of collecting and sorting grey numbers. Next, the prospect value function is determined in view of the decision-making information with different time points as the reference points. Then, an optimal model for solving the attribute weight and time weight is constructed based on the grey entropy principle. Findings The paper provides a dynamic grey interrelation decision method based on the prospect theory with three-parameter interval grey number, and the example analysis shows that the method proposed in this paper has validity and rationality. Research limitations/implications If we have a better understanding of the weights of different reference points, it is possible to receive a more reasonable expression for the comprehensive prospect utility value function. Practical implications The paper provides a grey interrelation decision method based on the prospect theory, which can help the decision maker deal with the dynamic multi-attribute decision-making problems under the uncertain environment. Originality/value The paper proposes the kernel and ranking method of three-parameter interval grey number, and uses different time points as the reference points to define the prospect value function. Furthermore, this paper structures a dynamic grey interrelation decision method with three-parameter interval grey number based on the prospect theory.

A comparative analysis of grey ranking approaches

2019 ◽  
Vol 9 (4) ◽  
pp. 472-487 ◽  
Author(s):  
Davood Darvishi ◽  
Jeffrey Forrest ◽  
Sifeng Liu
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Partial Order ◽  
Design Methodology ◽  
Total Order ◽  
Interval Numbers ◽  
Content Type ◽  
Important Decision ◽  
Grey Number ◽  
Order Kernel

Purpose Ranking and comparing grey numbers represent a very important decision-making procedure in any given grey environment. The purpose of this paper is to study the existing approaches of ordering interval grey numbers in the context of decision making by surveying existing definitions. Design/methodology/approach Different methods developed for comparing grey numbers are presented along with their disadvantages and advantages in terms of comparison outcomes. Practical examples are employed to show the importance and necessity of using appropriate methods to compare grey numbers. Findings Most the available methods are not suitable for pointing out which number is larger when the nuclei of the grey numbers of concern are the same. Also, these available methods are also considered in terms of partial order and total order. Kernel and degree of greyness of grey numbers method is more advantageous than other methods and almost eliminates the shortcomings of other methods. Originality/value Different methods for ranking grey numbers are presented where each of them has disadvantages and advantages. By using different methods, grey interval numbers are compared and the results show that some methods cannot make grey number comparisons in some situations. The authors intend to find a method that can compare grey numbers in any situation. The findings of this research can prevent errors that may occur based on inaccurate comparisons of grey numbers in decision making. There are various research studies on the comparison of grey numbers, but there is no research on the comparison of these methods and their disadvantages, advantages or their total or partial order.

Decision Method of Optimal Investment Enterprise Selection under Uncertain Information Environment

2015 ◽  
Vol 4 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Xiaoyong Liao
Keyword(s):  
Decision Making ◽  
Optimal Investment ◽  
Information Environment ◽  
Investment Risk ◽  
Uncertain Information ◽  
Fuzzy Information ◽  
Selection Decision ◽  
Deviation Degree ◽  
Grey Number ◽  
Decision Making Model

To select an optimal investment enterprise is the key to effectively reduce the investment risk for an investment company. In this paper, the author studies the problem of optimal investment enterprise selection decision under uncertain information environment (fuzzy information and grey information coexist), and present a fuzzy grey multi-attribute group decision making model to select the optimal investment enterprise. In this model, the author defines the concept and operations of fuzzy grey number, and present a ranking method based on fuzzy grey deviation degree to rank the alternative investment enterprises. The author also gives an application example of selecting optimal investment enterprise to highlight the implementation, availability, and feasibility of the proposed decision making model.

An enhanced algorithm for calculating the degree of greyness of interval grey numbers and its application

Kybernetes ◽  
2019 ◽  
Vol 49 (6) ◽  
pp. 1721-1740
Author(s):  
Shuaishuai Geng ◽  
Yu Feng ◽  
Yaoguo Dang ◽  
Junjie Wang ◽  
Rizwan Rasheed
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Decision Making Process ◽  
Content Type ◽  
Operational Mechanism ◽  
Operation Process ◽  
Algebraic Operations ◽  
Grey Number ◽  
Operation Results ◽  
Selection Of

Purpose This paper aims to propose an enhanced algorithm and used to decision-making that specifically focuses on the choice of a domain in the calculation of degree of greyness according to the principle of grey numbers operation. The domain means the emerging background of interval grey numbers, it is vital for the operational mechanism of such interval grey numbers. However, the criteria of selection of domain always remain same that is not only for the calculated grey numbers but also for the resultant grey numbers, which can be assumed as unrealistic up to a certain extent. Design/methodology/approach The existence of interval grey number operation based on kernel and the degree of greyness containing two calculation aspects, which are kernel and the degree of greyness. For the degree of greyness, it includes concepts of domain and calculation of the domain. The concepts of a domain are defined. The enhanced algorithm is also comprised of four deductive theorems and eight rules that are linked to the properties of the enhanced algorithm of the interval grey numbers based on the kernel and the degree of greyness. Findings Aiming to improve the algorithm of the degree of greyness for interval grey numbers, based on the variation of domain in the operation process, the degree of greyness of the operation result is defined in this paper, and the specific expressions for algebraic operations are given, which is relevant to the kernel, the degree of greyness and the domain. Then, these expressions are used to the algorithm of interval grey numbers based on the kernel and the degree of greyness, improving the accuracy of the operation results. Originality/value The enhanced algorithm in this paper can effectively reduce the loss of information in the operation process, so as to avoid the situation where the decision values are the same and scientific decisions cannot be made during the grey evaluation and decision-making process.

Sign in / Sign up

Export Citation Format

Share Document