A Non-Numeric Approach to Multi-Criteria/Multi-Expert Aggregation Based on Approximate Reasoning

TL;DR

This paper introduces a non-numeric, linguistically based aggregation method for multi-criteria and multi-expert decision-making, simplifying information fusion and consensus finding without relying on numerical data.

Contribution

It presents a novel approximate reasoning approach that handles nonnumeric linguistic information, differing importance levels, and expert consensus in decision processes.

Findings

Effective fusion of nonnumeric linguistic data

Ability to assign linguistic importance to criteria and sources

Successful application to project selection problem

Abstract

We describe a technique that can be used for the fusion of multiple sources of information as well as for the evaluation and selection of alternatives under multi-criteria. Three important properties contribute to the uniqueness of the technique introduced. The first is the ability to do all necessary operations and aggregations with information that is of a nonnumeric linguistic nature. This facility greatly reduces the burden on the providers of information, the experts. A second characterizing feature is the ability assign, again linguistically, differing importance to the criteria or in the case of information fusion to the individual sources of information. A third significant feature of the approach is its ability to be used as method to find a consensus of the opinion of multiple experts on the issue of concern. The techniques used in this approach are base on ideas developed from the theory of approximate reasoning. We illustrate the approach with a problem of project selection.