Research on Optimal Production Decision Based on Dynamic Programming Model

In the fiercely competitive machine parts manufacturing industry in China, companies must enhance production efficiency and reduce costs to maintain a competitive advantage. To achieve this, enterprises need to make optimal decisions during the production process to maximize profits. This paper proposes a decision-making framework aimed at addressing complex production and cost structures to ensure profit maximization under different conditions. A dynamic programming model is constructed to manage multi-stage decision-making, enabling enterprises to adjust strategies dynamically. To further improve decision outcomes, the simulated annealing algorithm is applied, which helps avoid local optima and identify the global optimal solution. The key innovation of this research is the integration of dynamic programming with the simulated annealing algorithm, offering significant flexibility and adaptability in optimizing complex production processes. This approach not only helps businesses improve efficiency, reduce costs, and strengthen their market competitiveness but also provides valuable insights for optimizing decision-making across the manufacturing industry.