Labour costs in the apparel manufacturing industry in Bangladesh have increased dramatically. Hence, there is no alternative way to optimize the apparel supply chain to survive in the competitive market. In this study, we implemented artificial neural networks (ANN) in apparel manufacturing organizations to optimize the supply chain by convergent on the right supplier selection by analyzing their performance criteria. Moreover, data was collected from three different factories to analyze the efficiency and profit-loss status of their units. Furthermore, analyze the supplier selection criteria of three suppliers in order to select the right supplier at the right time in the apparel manufacturing industry. This study shows that it can save 18% of the total cost. Additionally, the mathematical analysis has been performed to validate the data analysis for the right supplier selection based on the performance criteria.
Shibbir Ahmad and Mohammad Kamruzzaman (2022) Optimization in Apparel Supply Chain Using Artificial Neural Network, European Journal of Logistics, Purchasing and Supply Chain Management, Vol.10 No.1, pp.1-14
Keywords: Artificial Neural Network, Cost, profit, right supplier selection, supply chain optimization
