SELECTION OF SUSTAINABLE SUPPLIER(S) IN A PAINT MANUFACTURING COMPANY USING HYBRID META-HEURISTIC ALGORITHM

• M Machesa Department of Mechanical and Industrial Engineering, University of Johannesburg, South Africa https://orcid.org/0000-0002-3218-1825
• L Tartibu Department of Mechanical and Industrial Engineering, University of Johannesburg, South Africa http://orcid.org/0000-0003-2111-7155
• M Okwu Department of Mechanical and Industrial Engineering, University of Johannesburg, South Africa http://orcid.org/0000-0002-7761-9659

DOI:

https://doi.org/10.7166/31-3-2429

Keywords:

Supplier selection, Hybrid Algorithm, ANFIS, Supply chain

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 out-bound supply chain system.