An Extended TOPSIS Method for the Multiple Attribute Decision Making Problems Based on Interval Neutrosophic Set

Abstract

The interval neutrosophic set (INS) can be
easier to express the incomplete, indeterminate and
inconsistent information, and TOPSIS is one of the most
commonly used and effective method for multiple
attribute decision making, however, in general, it can
only process the attribute values with crisp numbers. In
this paper, we have extended TOPSIS to INS, and with
respect to the multiple attribute decision making
problems in which the attribute weights are unknown and
the attribute values take the form of INSs, we proposed
an expanded TOPSIS method. Firstly, the definition of
INS and the operational laws are given, and distance
between INSs is defined. Then, the attribute weights are
determined based on the Maximizing deviation method
and an extended TOPSIS method is developed to rank the
alternatives. Finally, an illustrative example is given to
verify the developed approach and to demonstrate its
practicality and effectiveness.