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This paper focuses on the multiple attribute decision making problems with the attribute values being numeric, interval and linguistic evaluations. The decision matrix is normalized by calculating the grey relation coefficients of the interval and linguistic attribute values to their corresponding positive ideal ones. Furthermore, a mathematical programming model is set up to figure out the attribute...
This paper focuses on the multiple attribute decision making problems with the attribute values being linguistic variables. The decision matrix is normalized by calculating the superiority possibility of the linguistic attribute values to their corresponding positive ideal ones. Furthermore, a mathematical programming model is set up to figure out the attribute weights with the overall values of the...
This paper proposes a grey relation-based approach to customer value assessment while customerspsila information is expressed in the form of interval numbers. By calculating the grey relation coefficient between interval attribute values and the ideal one, the decision matrix in the form of interval is transformed into a definite one, based on which the attribute weights are determined in order to...
This paper proposes a new approach to the uncertain multiple attribute decision making problems based on the grey-relation theory, where the attribute values in decision matrix is expressed in the form of intervals and definite values. In the approach, the attributes are classified into two categories: the definite and the interval. Based on the grey relation theory, the attribute values are normalized...
This paper focuses on the multiple attribute decision making problems with the attribute values being linguistic evaluations. The decision matrix is normalized by calculating the grey relation coefficients of linguistic attribute values to their corresponding positive ideal one. Furthermore, a mathematical programming model is set up to figure out the attribute weights with the overall values of the...
This paper focuses on the multiple attribute decision making problems with the attribute values being linguistic evaluations. The decision matrix is normalized by calculating the relative distance between the linguistic attribute values and their corresponding negative ideal one. Furthermore, a mathematical programming model is set up to figure out the attribute weights with the overall values of...
This paper proposes an approach to customer value assessment based on Max-Entropy and TOPSIS, while customerspsila information are interval numbers. The decision matrix in the form of interval is normalized and transformed into a definite one based on maximizing the entropy of the decision matrix; The weights of attributes are then determined, which are used in assessing the alternatives based on...
This paper proposes an integration approach to multiple attribute decision making with expertspsila preference information on alternatives. In the approach, expertspsila subjective preference information on robots is represented in preference orderings, utility values and fuzzy preference relation. By integrating the subjective information and the objective information (decision matrix), the new approach...
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