The power consumption in the process of silicon single crystal growth is huge, so the power load must be limited to a specific range to ensure the safe and stable operation on the silicon single crystal furnace. this This article establishes a two-objective mathematical model for the multi-furnace optimal scheduling problem in silicon single crystal production process. The first objective is to minimize the maximum completion time of silicon single crystal growth process on multi-furnaces, and the second objective is to minimize the maximum power consumption obtained by the multi-furnace operation together. A disturbed non-dominated sorting particle swarm optimization combined with genetic algorithm (DNSGPSO) is proposed to solve the multi-objective optimization problem. Through simulation analysis of actual growth data, the effectiveness of the proposed model and the superiority of the algorithm are verified.

单晶硅生长过程中的功耗巨大，因此必须将功率负载限制在特定范围内，以保证单晶硅炉安全稳定运行。本文针对单晶硅生产过程中的多炉优化调度问题建立了一个二目标数学模型。第一个目标是最小化多炉单晶硅生长过程的最大完成时间，第二个目标是最小化多炉操作所获得的最大功耗。针对多目标优化问题，提出了一种结合遗传算法的扰动非支配排序粒子群优化算法（DNSGPSO）。通过对实际增长数据的模拟分析，