The transformation method between the linguistic judgement matrix and other four forms of preference information is researched in this paper. The four forms of preference information are preference ordering, utility value, reciprocal judgement matrices and complementary judgement matrices. First, based on the definition of preference information, the mutual transformation methods of linguistic judgement matrix and other four forms of preference information are given. Then new transformation equations are obtained. Next, it is proved that when the linguistic judgement matrix has complete consistency, the other four forms of preference information will have complete consistency too. Finally, a numerical analysis is offered to show that these methods are feasible and effective.
Keywords
- group decision-making
- linguistic judgement matrix
- preference information
- consistency
Owing to differences in cultural background, psychological quality and life experience, different decision-makers in a group may have different individual preferences for the same decision-making problems, and their importance or authority may be different. The heterogeneity of decision-making groups in decision-making practice cannot be ignored. Therefore, the quest for the means to design a scientific, effective and rapid mechanical method for the different preference information given by heterogeneous groups is an urgent basic theoretical problem to be solved. The content of decision-makers’ perception of the external environment is diverse and the information involved is complex. There is also uncertainty in the process of different decision-makers’ perception of information. At the same time, the information itself also has a certain degree of randomness and conflict; so, it is necessary to unify different preference information.
With the development of group decision-making, different forms of preference information have arisen, including the initial preference order, utility value, reciprocal judgement matrix and complementary judgement matrix, but this preference information cannot meet the needs of decision-makers. Since Zadeh and Yager put forward the concept of using linguistic information to represent evaluation results [1, 2, 3, 4, 5, 6, 7], the linguistic judgement matrix has assumed importance as a vital mode of information provided by decision-makers to compare the two alternatives. Due to the complexity and fuzziness of decision-makers’ knowledge background and decision objects, decision-makers may give different forms of preference information for the same decision-making problem. In order to aggregate different preference information given by decision-makers, it is necessary to unify different forms of preference information. The research in this field has attracted extensive attention of scholars and achieved certain results [8, 9, 10, 11, 12, 13, 14, 15, 16]. The aggregation method of natural language and numerical preference information was given in Delgado et al. [8]; the conversion method of four kinds of preference information in group decision-making was given in the study by Wujiang [9]; Xiao et al. [10] study the conversion method of two kinds of preference information with reciprocal judgement matrix and fuzzy complementary judgement matrix in group decision-making; Huayou and Chunlin [11] give three kinds of preference information: order relation value, reciprocal judgement matrix and fuzzy complementary judgement matrix. The effectiveness of information transformation is calculated in the form of value. Most of these studies analyse the mutual transformation of four kinds of preference information, and seldom systematically study the mutual transformation between linguistic information and among them. Yan-Wu and Hua-You [12] transform linguistic judgement matrix into derived matrix, and prove that derived matrix is complementary judgement matrix, which is also equivalent to transforming linguistic judgement matrix into complementary judgement matrix. When the preference information given by experts consists of fuzzy complementary judgement matrix, interval value, positive reciprocal matrix, order relation value and utility value, the preference information of different forms is transformed into fuzzy complementary judgement matrix, and then the ranking value of each scheme is obtained according to the fuzzy complementary judgement matrix in the study by Yangjing [13].
A GDM framework based on consistency driven and consistency driven optimisation model of personalised normalisation method is proposed to manage complete and incomplete probabilistic linguistic preference relation in Tian et al. [15].
This paper presents the conversion formula between linguistic judgement matrix and four kinds of preference information, which mainly solves the problem of mutual conversion between linguistic information and among them, and theoretically proves the rationality of the conversion formula and the consistency after conversion. Finally, an example is used to verify the rationality and effectiveness of the conversion formula.
Orderliness: when Inverse operation neg: neg( Maximisation operation: if Minimisation operation: if
[13, 14, 15] Let
The definitions of linguistic information and four kinds of preference information are given as follows.
The preference information given by the decision-maker can be expressed by linguistic information. The preference information can be described by a matrix
The decision-maker directly gives the order of the decision alternative set according to the individual preference:
For the alternative set
The decision-maker compares the alternatives in the alternative set
The decision-maker compares the alternatives in the alternative set and gives complementary judgement matrix
In the case of strict preference relationship between each alternative, this paper discusses the consistency method of linguistic judgement matrix with the other four kinds of preference information, and assumes that linguistic judgement matrix has satisfactory consistency.
[13, 14]
Let
Let
In this way, the row preference value of each alternative can be obtained, and the preference order of the alternative s can be determined according to the size of the row preference value. If calculated by column, the result is just the opposite.
The smaller the value
When calculating the utility value of an alternative
Let
Then the conversion formula of the utility value obtained from the linguistic judgement matrix can be stated as follows:
The utility value is the preferred utility value given by the decision-maker. The larger the utility value, the better the alternative. The conversion formula of utility value into linguistic judgement matrix is given as follows:
Then, the linguistic judgement matrix is expressed as:
The elements of the reciprocal judgement matrix satisfy [1/9, 9] and
There is
So, the condition of reciprocal judgement matrix is satisfied.
When the reciprocal judgement matrix is transformed into the linguistic judgement matrix, the inverse function expressed in Eq. (8) is used as the conversion formula.
Then, the linguistic judgement matrix
Let the granularity of the phrase evaluation set on the linguistic judgement matrix
[13, 14] If the linguistic judgement matrix satisfies
[21] Let
Then
If the linguistic judgement matrix is completely consistent, then it is satisfied that
It is concluded that the reciprocal judgement matrix is also consistent.
Let the granularity of the linguistic phrase evaluation set of the linguistic judgement matrix be
So the condition of complementary judgement matrix is satisfied.
The inverse function expressed in Eq. (14) is used as the conversion function of the complementary judgement matrix to the linguistic judgement matrix, which is
Then the linguistic judgement matrix
[23] The complementary judgement matrix
Then the matrix is said to be completely consistent.
If the linguistic judgement matrix is completely consistent, then
So theorem 2 is proved.
This paper studies the mutual conversion between linguistic judgement matrix and other four kinds of preference information. To judge the order of alternatives, we transform the other decision preference information into the linguistic judgement matrix to judge the order of alternatives. The fifth decision-maker gives a linguistic judgement matrix based on a linguistic phrase evaluation set with a granularity of 9. The granularity of the linguistic phrase evaluation set used to transform other preference information into linguistic judgement matrix is also 9. According to the above transformation formula, the preference information is transformed into linguistic judgement matrix.
Using Eq. (3), the above linguistic judgement matrix is transformed into the following preference relation matrix:
We arrange the alternatives according to the number of 1 in the preference relation matrix. The order of
In this paper, the transform formula between linguistic judgement matrix and other four preference information (preference order, utility value, reciprocal judgement matrix and complementary judgement matrix) is given systematically, and the rationality of the transform formula is theoretically proved. This method provides the transformation of different preference information forms in group decision-making. Further, more detailed and accurate transform methods between preference information and its application need to be studied further.
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