Evaluation on Semiconductor Manufacturing Reconfiguration and Production Based on Scheduling Integrated Optimization Algorithm

The semiconductor manufacturing industry is currently one of the most important industries in the world. This article studies semiconductor manufacturing reconstruction and production based on scheduling integrated optimization algorithms, and models and analyzes the semiconductor manufacturing process. Using semiconductor wafer manufacturing production lines as the research object, a set of scheduling integrated optimization algorithms was designed to reduce manufacturing costs and improve production efficiency. The experimental results show that the genetic optimization algorithm saves 18 minutes more time than traditional scheduling algorithms when scheduling semiconductor manufacturing tasks, and the semiconductor production linearity generated by the genetic optimization algorithm can be closer to the optimal production performance line. The results indicate that the scheduling integrated genetic optimization algorithm can effectively improve semiconductor manufacturing efficiency and reduce manufacturing costs. In addition, many scheduling problems require real-time adjustment and dynamic scheduling to adapt to environmental and task changes, and scheduling integration methods based on genetic algorithms can dynamically adjust scheduling strategies and parameters based on real-time data and environmental changes, achieving real-time and dynamic tuning optimization.