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In spinning industries, selection of the most appropriate fibre for yarn manufacturing plays an important role for achieving an optimal mix of several yarn characteristics, like maximum tenacity, elasticity and spinning ability; and minimum unevenness and hairiness. Identification of the best suited cotton fibre from a set of available alternatives in presence of different conflicting physical properties is often treated as a multi-criteria decision-making (MCDM) problem. The paper aims to discuss this issue.

In this paper, the preference ranking organisation method for enrichment of evaluations (PROMETHEE) and geometrical analysis for interactive aid (GAIA) methods are integrated to solve a cotton fibre selection problem. The PROMETHEE II method ranks the alternative cotton fibres based on their net outranking flows, whereas GAIA acts as a visual aid to strongly support the derived selection decision. The weight stability intervals for all the considered fibre properties (criteria) over which the position of the top-ranked cotton fibre remains unchanged are also determined.

The clusters of cotton fibres formed in the developed GAIA plane act as a yard stick for their appropriate grading to aid the blending process. The ranking of 17 cotton fibres as achieved applying the combined PROMETHEE-GAIA approach highly corroborates with the observations of the past researchers which proves its immense potentiality and applicability in solving fibre selection problems.

Two MCDM methods in the form of PROMETHEE II and GAIA are integrated to provide a holistic approach for cotton fibre grading and selection while taking into consideration all the available cotton fibre properties.