Research on Improved Assembly Decision Optimization Model Based On Simulated Annealing Algorithm

With the rapid development of the economy and society, the demand for high-quality products has risen, and the connection between product quality and economic benefits is also more and more profound, making it crucial to balance economic benefits with minimizing defects in production. To improve both economic outcomes and product quality, this paper considers factors such as the defective rates of spare parts, semi-finished products, and finished products, as well as the cost of spare parts, inspection, and exchange losses. Using a simulation of real-world conditions, an optimization model is developed based on the simulated annealing algorithm, with the goal of maximizing benefits. The model proposes that finished products be inspected directly, without checking parts or semi-finished products, and defective products be discarded immediately to maximize profit. The significance of this study lies in its ability to optimize production decisions, enhancing both efficiency and profitability while maintaining product quality. The model has potential applications not only in the production scenario studied in this paper but also in fields such as logistics distribution and path planning, which can help improve operational efficiency and reduce costs.