A novel multi-criteria decision analysis technique incorporating demanding essential characteristics of existing MCDA techniques

A novel multi-criteria decision analysis technique incorporating demanding essential characteristics of existing MCDA techniques

연구 분야: Verification

학회: Progress in Artificial Intelligence

This paper has proposed a novel multi-criteria decision analysis (MCDA) technique that considers relationships among the criteria, relationships among the alternatives, relationships among the criteria and the alternatives, the uncertainty or dilemma that the decision makers face in their decision-making, the entropy among the criteria. These characteristics are the essential characteristics of various MCDA techniques as evident from the existing literature. Incorporating all these characteristics in a single algorithm is the novelty and unique contribution of the proposed technique in this paper. The existing MCDA techniques are based on individual characteristics such as distance measurement from the best solution, utility measurement, measuring kind of average values, pair-wise comparison and considerations of relationships among criteria. However, no single research study has considered the prime characteristics of these techniques through a single algorithm. This is the motivation behind the proposed technique. The dilemma of the decision makers has been captured by the use of hesitant fuzzy elements; the information content among the criteria has been captured by applying the concept of entropy through the application of a technique called IDOCRIW. Relationships have been determined by calculating covariances among the criteria and among the alternatives. A kind of sensitivity analysis, rank reversal method has been performed to verify the effectiveness of the proposed technique. The proposed method has also been compared with four different types of already existing MCDA techniques, AHP, MAUT, MACBETH and MOORA. Both the sensitivity analysis and the comparison with other methods establish the effectiveness of the proposed technique. The results of the comparison by these methods establish the superiority of the proposed MCDA technique over the existing techniques.