I am conducting analysis on 'Multi-Attribute Decision Making (MADM)', where I have two attributes (a1, a2) to characterize the quality of m alternative approaches. The first attribute, a1, is measured in percentage (hence does not have a unit), whereas the other has a unit. There are some alternatives that have zero as their first attribute value.
What I am aiming to do is to compare different alternatives and determine the 'best' alternative by assuming equal weighting of the attributes. I am aware that 'Multi-Attribute Decision Making' methods may yield to the problem called 'rank reversal' (i.e. ranking of the alternatives may change by adding new alternatives). However, as far as I understood (and tested), 'Weighted Product Model (1)' does not suffer from this issue. The issue that arise; however, is that I cannot directly use this method as it requires division of the scores of different alternatives.
I thought of increasing all the a1 values by a certain amount and it seems to be working fine. However, if I increase the a1 values more than a value, then rankings start to change. Do you know any other ways to use 'Weighted Product Model' to evaluate alternatives on the presence of zeros?
Reference: (1) Triantaphyllou, E. & Mann, S.H., 1989. An examination of the effectiveness of multi-dimensional decision-making methods: A decision-making paradox. Decision Support Systems, 5(3), pp.303–312.