De-Novo Approach in Rank Agglomeration in Multi Criteria Decision Making for Materials Selection
Abstract
Multiple criteria decision making (MCDM) has proven to be a highly effective technique in recent years for determining the relative acceptability of a set of competing alternatives based on a set of criteria. Each technique has its own logical and mathematical foundations, as well as distinct procedures. When different approaches yield vastly different rankings, ambiguity arises. Therefore, this proposal aims to address this issue in determining an aggregate rank by combining the results of various approaches. In this method, an initial rank is calculated by averaging the ranks, and the deviation of each rank from the average is then determined. The weighted average rank is subsequently computed using Proximity Indices and Dynamic Weights, which are based on rank deviations. The rank is then checked to see if it aligns with the average rank. If it does, the process continues until the ranking orders in two subsequent iterations match. To illustrate the scope of this approach, a relevant example is provided, which is deemed adequate for this purpose.