Abstract
Businesses that deal with putrescible products have to maintain their inventories at an optimal level as the shortage of products or excess of products can incur losses; hence, optimization of inventories is a very crucial task in supply chain management. To minimize the effect of surplus as well as shortage on the businesses, inventory optimization management software helps to minimize the loss due to this supply chain problem. Exploration for this study is done using various machine learning algorithms to forecast the quantity required for a supermarket to sustain its future sales for the next day. This study aims to support a retail company in its demand–supply chain, and thus for this study, a public dataset of supermart has been used.
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Gurnani, P., Hariani, D., Kalani, K., Mirchandani, P., CS, L. (2022). Inventory Optimization Using Machine Learning Algorithms. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-6460-1_41
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DOI: https://doi.org/10.1007/978-981-16-6460-1_41
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