Efficient pairwise preference elicitation allowing for indifference

Many methods in Multi-Criteria Decision Analysis for choice problems rely
on eliciting pairwise preference information in their attempt to eciently
identify the most preferred solution out of a larger set of solutions. That is,
they repeatedly ask the decision maker which of two solutions is preferred,
and then use this information to reduce the number of possibly preferred
solutions until only one remains. However, if the solutions have a very similar
value to the decision maker, he/she may not be able to accurately decide
which solution is preferred. This paper makes two main contributions. First,
it extends Robust Ordinal Regression to allow a user to declare indierence in
case the values of the two solutions do not dier by more than some personal
threshold. Second, we propose and compare several heuristics to pick pairs of
solutions to be shown to the decision maker in order to minimize the number
of interactions necessary.