4 The Technique For Order of Preference by Similarity …
27
However, the shortcoming of TOPSIS includes;
• There might be a weights calculated utilizing AHP or fuzzy logic and later
TOPSIS.
• It is difficult to weight as well as keeping the consistency of judgment.
• Euclidean distance’s application does not correlate with attributes (Robbi Rahim
2018).
• It is highly subjective (Sharma et al. 2020)
In TOPSIS there is no any capacity restriction, which ease the decision maker
work. It is applicable where the huge number of the criteria and alternatives arises
specifically if there is objective or quantitative information available for the case.
Generally, the TOPSIS methods algorithms begin with obtaining the decision
matrix which represents the combination of the criteria of each alternative. Also, the
framework is normalized with one of the normalization technique, and the normalized
values are multiplied by the importance weights of their corresponding criteria. Along
these lines, the PIS and NIS are arranged, then separate measures of each alternative
to these arrangements are calculated based on a distance degree. Lastly, the choices
are positioned related to their relative closeness to the PIS. The TOPSIS procedure is
accommodating for choice producers to structure the issues to be optimized, conduct
investigations, comparisons and positioning of the choices.
The classic method of TOPSIS consists issues where the chosen comparative
information are known and presented numerically. In reality, the problems of the
world are mostly very complex, which is not easy to model since there is many affect
even the decision maker cannot be aware to consider, or suddenly some situations
can change, which should be considered in the model to increase its effectiveness.
The hybrid applications of the classic TOPSIS method with other extensional models
such as; where there is the interval in decision matrix arise or fuzzy criteria while
defining the vagueness of the problem, are the new approach that started to be studied
by many researcher.
Interval investigation may be a basic and instinctive way to present information,
instability for complex choice issues, and can be utilized for numerous viable applications. An expansion of the TOPSIS method to a gather choice environment is
additionally explored. The setting of multi-criteria decision-making in vague and
interval information could need a hybrid methodology, first the arrangement of the
data and then the analysis of the ranking. TOPSIS strategy can only be applied where
the decision matrix and importance weights of the criteria supposed to be defined as
the numerical data.
4.1.1 Mathematical Framework of the TOPSIS Method
To understand this technique and see how it can be applied, it is important to analyze
each step consecutively as shown below (Yahya et al. 2020).
27
However, the shortcoming of TOPSIS includes;
• There might be a weights calculated utilizing AHP or fuzzy logic and later
TOPSIS.
• It is difficult to weight as well as keeping the consistency of judgment.
• Euclidean distance’s application does not correlate with attributes (Robbi Rahim
2018).
• It is highly subjective (Sharma et al. 2020)
In TOPSIS there is no any capacity restriction, which ease the decision maker
work. It is applicable where the huge number of the criteria and alternatives arises
specifically if there is objective or quantitative information available for the case.
Generally, the TOPSIS methods algorithms begin with obtaining the decision
matrix which represents the combination of the criteria of each alternative. Also, the
framework is normalized with one of the normalization technique, and the normalized
values are multiplied by the importance weights of their corresponding criteria. Along
these lines, the PIS and NIS are arranged, then separate measures of each alternative
to these arrangements are calculated based on a distance degree. Lastly, the choices
are positioned related to their relative closeness to the PIS. The TOPSIS procedure is
accommodating for choice producers to structure the issues to be optimized, conduct
investigations, comparisons and positioning of the choices.
The classic method of TOPSIS consists issues where the chosen comparative
information are known and presented numerically. In reality, the problems of the
world are mostly very complex, which is not easy to model since there is many affect
even the decision maker cannot be aware to consider, or suddenly some situations
can change, which should be considered in the model to increase its effectiveness.
The hybrid applications of the classic TOPSIS method with other extensional models
such as; where there is the interval in decision matrix arise or fuzzy criteria while
defining the vagueness of the problem, are the new approach that started to be studied
by many researcher.
Interval investigation may be a basic and instinctive way to present information,
instability for complex choice issues, and can be utilized for numerous viable applications. An expansion of the TOPSIS method to a gather choice environment is
additionally explored. The setting of multi-criteria decision-making in vague and
interval information could need a hybrid methodology, first the arrangement of the
data and then the analysis of the ranking. TOPSIS strategy can only be applied where
the decision matrix and importance weights of the criteria supposed to be defined as
the numerical data.
4.1.1 Mathematical Framework of the TOPSIS Method
To understand this technique and see how it can be applied, it is important to analyze
each step consecutively as shown below (Yahya et al. 2020).