Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Aggregation of fuzzy opinions under group decision making
Fuzzy Sets and Systems
Combining belief functions when evidence conflicts
Decision Support Systems
Combining belief functions based on distance of evidence
Decision Support Systems
Computers and Operations Research
Journal of Management Information Systems
Risk assessment based on weak information using belief functions: a case study in water treatment
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Evaluating Sensor Reliability in Classification Problems Based on Evidence Theory
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fuzzy risk analysis based on similarity measures of generalized fuzzy numbers
IEEE Transactions on Fuzzy Systems
Assessment of E-Commerce security using AHP and evidential reasoning
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Knowledge-Based Systems
A biologically inspired solution for fuzzy shortest path problems
Applied Soft Computing
A new method to determine basic probability assignment from training data
Knowledge-Based Systems
A study of TODIM in a intuitionistic fuzzy and random environment
Expert Systems with Applications: An International Journal
Supplier selection using AHP methodology extended by D numbers
Expert Systems with Applications: An International Journal
Environmental impact assessment based on D numbers
Expert Systems with Applications: An International Journal
The QoS-based MCDM system for SaaS ERP applications with Social Network
The Journal of Supercomputing
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Multiple-criteria decision-making (MCDM) is concerned with the ranking of decision alternatives based on preference judgements made on decision alternatives over a number of criteria. First, taking advantage of data fusion technology to comprehensively consider each criterion data is a reasonable idea to solve the MCDM problem. Second, in order to efficiently handle uncertain information in the process of decision making, some well developed mathematical tools, such as fuzzy sets theory and Dempster Shafer theory of evidence, are used to deal with MCDM. Based on the two main reasons above, a new fuzzy evidential MCDM method under uncertain environments is proposed. The rating of the criteria and the importance weight of the criteria are given by experts' judgments, represented by triangular fuzzy numbers. Then, the weights are transformed into discounting coefficients and the ratings are transformed into basic probability assignments. The final results can be obtained through the Dempster rule of combination in a simple and straight way. A numerical example to select plant location is used to illustrate the efficiency of the proposed method.