Solving supplier selection problem in a textile industry using an integrated grey-MABAC method

Like other industries, selection of suppliers in a textile mill also plays a decisive role by providing right quality of raw materials/components/dyes and chemicals in right quantities at right time and affordable cost, thereby establishing an effective supply chain. Acknowledging supplier selection/evaluation as a multi-criteria decision-making (MCDM) problem, various mathematical tools have been proposed to resolve the issue. In this paper, a grey-based MCDM approach, i.e. grey-multi-attributive border approximation area comparison (G-MABAC) method is proposed for solving a textile supplier selection problem, expressing relative importance of the decision makers, criteria and alternatives using grey numbers. Based on the performance scores, G-MABAC partitions six alternative suppliers into upper approximation (reliable) and lower approximation (unreliable) areas, identifying the relative strengths and weaknesses of each of them. It would act as an intelligent decision support framework in effectively adopting multi-sourcing strategy for enhanced resilience with minimum disruption in the textile supply chain.