<![CDATA[Production planning and inventory control are crucial factors in improving a company's operational efficiency, particularly in the face of fluctuating demand and limited production capacity. Inaccuracy in determining production quantities and timing can lead to overstocks, stockouts, and increased inventory costs. One optimization approach capable of addressing these issues is dynamic programming, a multistage decision-making method that considers the interrelationships between periods. This study aims to examine the application of dynamic programming in optimizing production planning and inventory control based on previous research findings. The research method used is a literature review, reviewing relevant scientific journals, proceedings, and academic books from the past ten years. The study results indicate that dynamic programming is effective in reducing total production and inventory costs, improving material planning accuracy, and optimizing production and ordering policies in various industrial sectors. Models such as the Wagner–Whitin model have been shown to optimally address warehouse capacity limitations and demand fluctuations. Thus, dynamic programming is an adaptive and applicable approach to support modern production planning decision-making, which demands efficiency, flexibility, and cost accuracy.  ]]>
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