A Mathematical Programming Model to Determine Objective Weights for the Interval Extension of TOPSIS

Abstract EN

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method has been extended in previous literature to consider the situation with interval input data.

However, the weights associated with criteria are still subjectively assigned by decision makers.

This paper develops a mathematical programming model to determine objective weights for the implementation of interval extension of TOPSIS.

Our method not only takes into account the optimization of interval-valued Multiple Criteria Decision Making (MCDM) problems, but also determines the weights only based upon the data set itself.

An illustrative example is performed to compare our results with that of existing literature.