Inventory Optimization Model Design with Machine Learning Approach in Feed Mill Company

Alfian Aziz Nasution, N. Matondang, A. Ishak
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Abstract

This article aims to address the impacts that companies can have with the application of machine learning to carry out their demand forecasts, knowing that a more accurate demand forecast improves the performance of companies, making them more competitive. The methodology used was a literature review through descriptive, qualitative and with bibliographical surveys in International Journal from 2010 – 2022 by different authors. Findings show that the references prove that demand forecasting with the use of machine learning brings many benefits to organizations, for example, since the results are more accurate, there is better inventory management, consequently customer satisfaction for having the product at the right time and place. Further, this article concludes and suggests that the use of machine learning is able to identify variables that affect the demands, with this it makes a forecast closer to reality and helps managers to make more accurate decisions, improving strategic planning and supply chain management. of company supplies.
基于机器学习的饲料厂库存优化模型设计
本文旨在解决公司应用机器学习来进行需求预测的影响,因为更准确的需求预测可以提高公司的绩效,使其更具竞争力。使用的方法是通过描述,定性和书目调查的文献综述国际期刊从2010年至2022年由不同的作者。研究结果表明,参考文献证明,使用机器学习的需求预测给组织带来了许多好处,例如,由于结果更准确,有更好的库存管理,因此客户对在正确的时间和地点拥有产品感到满意。此外,本文总结并建议使用机器学习能够识别影响需求的变量,从而使预测更接近现实,并帮助管理人员做出更准确的决策,改进战略规划和供应链管理。公司的供应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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