A New Linguistic Scale for Interval Type-2 Trapezoidal Fuzzy Number based Multiple Criteria Decision Making Method
Decision making is a process for managing the decision problem for human beings that use linguistic information. However, it is sometimes limited by the fact that the linguistic models use only positive linguistic terms, which may not reflect exactly what the experts mean. The previous studies...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.unisza.edu.my/531/1/FH03-FIK-16-05791.jpg http://eprints.unisza.edu.my/531/ |
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| Summary: | Decision making is a process for managing the
decision problem for human beings that use linguistic
information. However, it is sometimes limited by the fact that the
linguistic models use only positive linguistic terms, which may
not reflect exactly what the experts mean. The previous studies
neglected the equilibrium concept (i.e., two sides of a matter) that
takes its roots from the Yin Yang theory. The Yin Yang theory
philosophically deals with two sides of things in the universe, and
focuses on the balance of the two sides. Thus, the purpose of this
paper is to introduce the new linguistic scales of positive and
negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN)
to the decision environment of interval type-2 fuzzy context for
solving Interval Type-2 Fuzzy Technique for Order Preference
by Similarity to Ideal Solution (IT2FTOPSIS) problems. This
new linguistic scales reacts to the subjective judgments from the
experts where the lowest of the scale and the highest of the scale
are equally strong. In decision making, it is rare to find the
negative scale, where it actually does not mean wrong or corrupt.
Here, the negative data represents a hypothesis that can make it
well-separated. The positive and negative are relatives. Along
with considering the context of the new linguistic scale, this paper
employs a hybrid averaging approach with ambiguity method
and type-reduction method to formulate a collective decision
environment. This hybrid averaging approach helps to reduce
values of Interval Type-2 Fuzzy Sets (IT2FS) to a crisp number.
The feasibility and applicability of the proposed methods are
illustrated with an example. |
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