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Optimization in Apparel Supply Chain Using Artificial Neural Network

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dc.contributor.author Ahmad, Shibbir
dc.contributor.author Kamruzzaman, Mohammad
dc.date.accessioned 2022-01-28T19:38:37Z
dc.date.available 2022-01-28T19:38:37Z
dc.date.issued 2022 en_US
dc.identifier.uri https://hdl.handle.net/10535/10838
dc.description.abstract 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. en_US
dc.language English en_US
dc.subject Supply Chain en_US
dc.subject.classification Management en_US
dc.title Optimization in Apparel Supply Chain Using Artificial Neural Network en_US
dc.type Journal Article en_US
dc.type.published published en_US
dc.type.methodology Modeling en_US
dc.publisher.workingpaperseries European Centre for Research Training and Development en_US
dc.coverage.region East Asia en_US
dc.coverage.country UK en_US
dc.identifier.citationjournal European Journal of Logistics, Purchasing and Supply Chain Management en_US
dc.identifier.citationvolume 10 en_US
dc.identifier.citationpages 1-14 en_US
dc.identifier.citationnumber 1 en_US

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