Application of Choquet Integral Operator to Aggregate ELICIT Information

Abstract

In real world it is commons to find decision making problems with uncertain information. The fuzzy linguistic approach has been successfully used to model this uncertainty through linguistic variables. There are different linguistic computational models based on the fuzzy linguistic approach, but most of them have some limitations. Recently, the Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT), has been proposed to model experts’ hesitation by comparative linguistic expressions, and a computational model has been introduced, which obtains interpretable and accurate results. The information fusion of linguistic values plays a pivotal role in the design of decision making algorithms. Keep in this view, several aggregation operators have been developed to fuse ELICIT information. However, the diverse characteristics of the decision making contexts and its modeling force the need for a new aggregation framework to fuse ELICIT information. This contribution aims at studying decision making problems with interactive criteria and develops an aggregation framework based on Choquet integral to aggregate ELICIT information capturing the interaction between criteria. Based on the proposed aggregation operator, a new solving method for Multi-Criteria Decision Making (MCDM) is presented. Finally, the practicality and feasibility of applying Choquet integral to ELICIT information is shown by an illustrative example.