Application of multi-objective optimization on the basis of ratio analysis (MOORA) for selection of cotton fabrics for optimal thermal comfort

Abstract

Purpose

Selection of fabrics for particular purposy-e has created lots of research interest over the years, and the said problems have been addressed by several researchers using various multi-criteria decision-making (MCDM) methods. The main purpose of this paper is to highlight a maiden approach to handle one such fabric selection problem using multi-objective optimization by ratio analysis (MOORA) as a simple yet potent MCDM tool.

Design/methodology/approach

Two approaches of MOORA method (namely, ratio system and reference point) have been demonstrated for ranking of 13 candidate fabrics based on four fabric attributes, namely, fabric cover, thickness, areal density and porosity.

Findings

In both the approaches, candidate fabric F3 secures rank 1 (the best alternative) whereas fabric F6 occupies rank 13 (the worst alternative). Moreover, ranking orders of these two approaches are alike and also show very high level of congruence with those of other approaches reported by earlier researchers, as evidenced from extremely high rank correlation coefficients (R_s > 0.89). During sensitivity analysis, each of the ranking results obtained from the four simulated weight sets do demonstrate very high degree of correlation (R_s > 0.90 for ratio system, and R_s > 0.81 for reference point). Besides, no occurrence of rank reversal is observed even when the initial decision-making matrix is changed.

Originality/value

Most the methods adopted so far for fabric selection purpose involve huge mathematical equations, complex computation and/or logic. The uniqueness of the MOORA method is that it involves minimal and thus very simple mathematical operations although possesses higher level of robustness and reliability.

Citation

Mitra, A. (2022), "Application of multi-objective optimization on the basis of ratio analysis (MOORA) for selection of cotton fabrics for optimal thermal comfort", Research Journal of Textile and Apparel, Vol. 26 No. 2, pp. 187-203. https://doi.org/10.1108/RJTA-02-2021-0021