Interval multi-objective optimization problems are ubiquitous and important in real-world applications. An
interactive evolutionary algorithm incorporating an optimization-cum-decision-making procedure is presented to obtain the
most preferred solution that fits a decision-maker(DM)’s preferences. In this algorithm, a preference direction is elicited by
requesting the DM to select the worst one from a part of non-dominated solutions. A metric based on the above direction,
which reflects the approximation performance of a candidate solution, is designed to rank different solutions with the same
rank and preference. The proposed method is applied to four interval bi-objective optimization problems, and compared
with PPIMOEA as well as a posteriori method. The experimental results show the effectiveness and high efficiency of the
proposed method.