Optimization in Apparel Supply Chain Using Artificial Neural Network

dc.contributor.authorAhmad, Shibbir
dc.contributor.authorKamruzzaman, Mohammad
dc.coverage.countryUKen_US
dc.coverage.regionEast Asiaen_US
dc.date.accessioned2022-01-28T19:38:37Z
dc.date.available2022-01-28T19:38:37Z
dc.date.issued2022en_US
dc.description.abstractLabour 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.identifier.citationjournalEuropean Journal of Logistics, Purchasing and Supply Chain Managementen_US
dc.identifier.citationnumber1en_US
dc.identifier.citationpages1-14en_US
dc.identifier.citationvolume10en_US
dc.identifier.urihttps://hdl.handle.net/10535/10838
dc.languageEnglishen_US
dc.publisher.workingpaperseriesEuropean Centre for Research Training and Developmenten_US
dc.subjectSupply Chainen_US
dc.subject.classificationManagementen_US
dc.titleOptimization in Apparel Supply Chain Using Artificial Neural Networken_US
dc.typeJournal Articleen_US
dc.type.methodologyModelingen_US
dc.type.publishedpublisheden_US

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