Selection of sustainable supplier(S) in a paint manufacturing company using hybrid meta-heuristic algorithm

Abstract

Supplier selection in a manufacturing system is highly complex owing to the nature and structure of organisations, necessitating a paradigm shift from the rule-of-thumb and classical methods of supplier selection to a reliable technique that uses a hybrid algorithm to provide greater accuracy in the selection process. This study proposes the use of a hybrid computational intelligence technique — an adaptive neuro-fuzzy inference system — for the effective identification and selection of sustainable suppliers. This hybrid modelling configuration was applied in a paint manufacturing company to select the best possible supplier. Information obtained from the company within the period of investigation was fed into the model. The result obtained shows a faster and more reliable prediction by the creative model. Professionals and business managers will benefit greatly from the selection of sustainable suppliers in an in-bound and outbound supply chain system.