Indifference mapping for multiple criteria decisions

Indifference mapping uses multi dimensional scaling techniques to allocate multi criteria policies to points in a space based on an input which consists of those pairs of policies which are equally attractive. The paper takes sets of policies for each of which a single value has been pre-assigned and maps them in two dimensions by applying a probability law to the assessment of indifferent pairs. The paper shows that the maps can be used both to deduce the original value of each policy and can also deduce the probability law which was applied.