Two Applications of Inter-Criteria Analysis with Belief Functions

Abstract

In this paper we present two applications of a new Belief Function-based Inter-Criteria Analysis (BF-ICrA) approach for the assessment of redundancy of criteria involved in Multi-Criteria Decision-Making (MCDM) problems. This BF-ICrA method allows to simplify the original MCDM problem by suppressing redundant criteria (if any) and thus diminish the complexity of MCDM problem. This approach is appealing for solving large MCDM problems whose solution requires the fusion of many belief functions. We show how this approach can be used in two distinct fields of applications: The GPS surveying problem, and the car selection problem.