MADM is one of the decision making methods to choose the alternative under multiple attributes . Since a number of conflict factors are caused by the limited resources, MADM allows a decision maker to determine the factor among the variables with multi-attribute or the optimal environment to operation situation.
Various MADM methods have been proposed to solve diverse applications of decision problems. One of MADM methods is Simple Additive Weighting (SAW). This method is also known as a weighted linear combination or scoring method
The SAW method was first introduced by Harsanyi. The SAW (Simple Additive Weighted) method is probably the best known and widely used method for some of the MADM decision making attributes Because of its simplicity, SAW is the most popular method in MADM problems.
The step wise procedure is given below:
There are several steps that must be taken in performing SAW calculation, such as:
Define criteria as an appraiser to the advantages of a variable.
Determine the match rate for each alternative for the criteria provided.
Create a decision matrix based on criteria.
Perform normalization based on benefits and cost on each attribute.
Determining the final value based on the defining weights for each R value on the normalization matrix
Advantages of SAW
• One of the advantages of this method is that it is a proportional linear transformation
of the raw data which means that the relative order of magnitude of the
standardized scores remains equal.
• For the solution of various problems, SAW is used as an important tool
in integrated approaches along with sensitivity analysis, TOPSIS, statistical
Limitations of SAW
• It does not account for fuzziness in experts’ judgements in the decision-making
• Its internal validity is affected by self-assessment bias.
• It demands all the criteria to be of maximizing nature. This is a drawback of this
method, though minimizing criteria can be easily converted to the maximizing
• It demands all criteria values to be positive.
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