Induced generalized Choquet aggregating operators with linguistic information and their application to multiple attribute decision making based on the intelligent computing
Affiliations: School of Astronautics, Northwestern Polytechnical University, Xi-An, Shaan Xi, China | Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada | Science and Technology on Aerospace Flight Dynamics Laboratory, Xi-An, Shaan Xi, China
Abstract: In this paper, we investigate the multiple attribute decision making problems in which the attribute weights are usually correlative, attribute values take the form of linguistic variables, some new methods are developed. Then a new aggregation operator called induced generalized 2-tuple linguistic choquet ordered averaging (IG-2TCOA) operator is proposed, and some desirable properties of the IG-2TCOA operator are studied, such as idempotent, commutative, monotonic and bounded. An IG-2TCOA operators-based approach is developed to solve the MADM problems. Finally, an illustrative example for evaluating the performance of the mechanical products is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Keywords: Multiple attribute decision making (MADM), 2-tuple linguistic variables, Choquet Integral, induced generalized 2-tuple linguistic choquet ordered averaging (IG-2TCOA) operator, mechanical products
