ABSTRACT
Entropy weights are the measures of uncertainties in the information formulated using probability theory. It indicates that a wide distribution represents more uncertainty than does a sharply peaked one. Entropy weights measure the information content in the attribute values of the alternatives, thereby evaluating each attribute’s usefulness in detecting differences in the data. The decision-making trial and evaluation laboratory method is used to perceive intricate relationships and build a network relation map between criteria. It was mainly developed by the Battelle memorial association of the Geneva research center to study complicated problems concerning about race, hunger, environmental protection, energy, etc. It is based on a concept of pair-wise comparison of decision-making attributes. The stepwise weight assessment ratio analysis method has become a popular approach for estimating criteria weights in MCDM problems.
