Enhancement of TOPSIS using compound linguistic ordinal scale and cognitive pairwise comparison

Abstract

TOPSIS is one of the popular multi-criteria decision making models. However, the determinations of the parametric settings of the rating scale and the weights for the decision matrix are still uncertain in TOPSIS. This research proposes the compound linguistic ordinal scale (CLOS) as the rating scale for the subject measure, and the cognitive pairwise comparison (CPC) for determining the weight. The usability and applicability of the enhanced TOPSIS are illustrated in a case of the robot selection problem.