ABSTRACT
The OCRA method was initially introduced to evaluate the performance measure of a set of production units that consumes resources to create value-added products. The first step towards the application of this method is to determine preference ratings of the non-beneficial or input criteria. The second step is to determine the preference ratings of the output criteria. In the third or final step, the overall preference ratings of the feasible alternatives are calculated considering both the cardinal and ordinal data. This method takes into consideration the decision maker’s instinctual preferences in terms of the relative significance of the criteria [1]. The estimated preference ratings of the considered alternatives reflect the preference of the decision maker for the criteria. In addition to this, the main benefit of this method is that it can take care of those MCDM situations where the relative criteria weights are dependent on the alternatives along with different weight distributions being allotted to the criteria for different alternatives, and few of these criteria are not relevant to the candidate alternatives.
