Saw Index -

Identify the options to be evaluated and the criteria (attributes) to be used.

Since criteria often have different units (e.g., dollars, weight, time), they must be normalized into a dimensionless scale, typically ranging from 0 to 1. Benefit Criteria: Higher values are better (e.g., profit). Cost Criteria: Lower values are better (e.g., risk, cost). Assigning Weights: Decision-makers assign a weight ( saw index

Data scientists often compare the SAW index with (Technique for Order of Preference by Similarity to Ideal Solution). Both create rankings, but their underlying philosophies differ. TOPSIS Method Core Concept Based on weighted average performance scores. Based on minimizing distance to the ideal best solution. Complexity Simple, intuitive linear mathematics. Identify the options to be evaluated and the