Extensions of the TOPSIS for group decision-making under fuzzy environment
Fuzzy Sets and Systems
Inter-company comparison using modified TOPSIS with objective weights
Computers and Operations Research
Facility location selection using fuzzy topsis under group decisions
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Generalizing TOPSIS for fuzzy multiple-criteria group decision-making
Computers & Mathematics with Applications
A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Failure mode and effects analysis using a group-based evidential reasoning approach
Computers and Operations Research
An evidential reasoning based approach for quality function deployment under uncertainty
Expert Systems with Applications: An International Journal
Weapon selection using the AHP and TOPSIS methods under fuzzy environment
Expert Systems with Applications: An International Journal
Customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Developing a fuzzy TOPSIS approach based on subjective weights and objective weights
Expert Systems with Applications: An International Journal
IEEE Transactions on Fuzzy Systems
On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An extension of TOPSIS for group decision making
Mathematical and Computer Modelling: An International Journal
Combining grey relation and TOPSIS concepts for selecting an expatriate host country
Mathematical and Computer Modelling: An International Journal
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TOPSIS is one of the major techniques in dealing with multiple criteria decision making (MCDM) problems, and Belief Structure (BS) model and Fuzzy BS model have been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with Fuzzy BS model is proposed to solve Group Belief MCDM problems. Firstly, the Group Belief MCDM problem is structured as a fuzzy belief decision matrix in which the judgments of each decision maker are described as Fuzzy BS models, and then the Evidential Reasoning approach is used for aggregating the multiple decision makers' judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. In order to measure the separation from the ideal belief solutions, the concept and algorithm of Belief Distance Measure are introduced to compare the difference between Fuzzy BS models. Using the Belief Distance Measure, the relative closeness and ranking index can be calculated for ranking the alternatives. A numerical example is finally given to illustrate the proposed method.