A case-based distance approach to multiple criteria ranking

A case-based distance approach is proposed to handle the multiple-criteria ranking problem, and a numerical example is presented to demonstrate the procedure and compare it with other approaches to ranking in multiple criteria decision analysis (MCDA). There are two general approaches to preference elicitation in MCDA, direct judgment and case-based. In direct judgement, the decision maker (DM) must explicitly supply all of the parameters of a preference model. In a case-based approach, the DM furnishes decisions on representative cases; then optimization programming finds the preference parameters best describing the representative decisions. A case-based distance approach that carries out multiple-criteria ranking is developed in this paper. Application to a numerical example not only demonstrates the feasibility of the procedure, but also shows that it is compatible with other approaches.