Abstract
ABSTRACT In this paper, a relatively new and mathematically potent tool of MCDM (Multi-Criteria Decision Making) in the form of EDAS (Evaluation based on Distance from Average Solution) approach has been proposed for ranking of thirteen candidate cotton fabrics on the basis of four fabric parameters/attributes namely cover, thickness, areal density, and porosity. The ranking and selection of the candidate fabrics have been done with a view to achieving optimal thermal comfort properties. Sample no. 3 with highest appraisal score of 0.9838 achieves rank 1 (best choice) whereas sample no. 6 with lowest appraisal score of 0.0000 occupies rank 13 (worst choice). The ranking results obtained by the proposed method demonstrates a significant agreement in ranking performance with the earlier methods, which is evidenced by very high rank correlation coefficients (Rs >0.87). Ranking patterns given by four imaginary weight sets also possess very high degree of agreement with rank correlation coefficients higher than 0.90. Moreover, there is no occurrence of rank reversal even when the initial decision-making matrix is changed. Thus, sensitivity analyses based on changing the criteria weights and that through influence of dynamic decision matrices further bolster the stability and robustness of the proposed approach in terms of ranking performance.
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