晶圆制造过程具有多模块协同、强时序约束等特征,传统方法在高混合生产场景下面临适应性差、约束协同困难等问题。针对严格准时制(JIT)约束下晶圆制造动态调度难题,提出一种基于遗传算法的高效动态调度方案—GA-JIT Scheduler,通过有向图建模将JIT等复杂约束编码至适应度函数,结合时间窗口检测与遗传进化策略,构建“感知-决策-执行”闭环调优机制,实现对动态扰动的快速响应。以“第九届集创赛·北方华创杯”4个差异化调度任务验证GA-JIT Scheduler,测得4个任务求解时间分别为93 256.5 s、15 311.5 s、13 013.5 s、18 470 s。该算法满足设备独占性及JIT(移动≤30 s、驻留≤15 s)约束,适配多场景,验证了其在严格JIT约束下晶圆制造动态调度的工程适用性与扩展性,为高混合、强时序约束的晶圆制造提供可行方案。

Wafer manufacturing involves multi-module coordination and strong temporal constraints. Traditional scheduling methods struggle in high-mix production scenarios due to poor adaptability and difficulty in handling complex constraints. To address the dynamic scheduling challenges under strict Just-in-Time (JIT) constraints, this paper proposes an efficient dynamic scheduling scheme named GA-JIT Scheduler, based on a genetic algorithm. The approach models equipment and processes using directed graphs, encoding JIT and other complex constraints into a fitness function. By integrating time-window detection and genetic evolution strategies, a "perception-decision-execution" closed-loop tuning mechanism is constructed to enable rapid responses to dynamic disturbances. This paper verifies the GA-JIT Scheduler using 4 differentiated scheduling tasks from the "9th National Innovation Competition (BeiFang HuaChuang Cup)", with the measured solution times of the four tasks being 93 256.5 s, 15 311.5 s, 13 013.5 s, and 18 470 s respectively. The algorithm satisfies constraints such as equipment exclusivity and JIT (movement≤30 s, residence time ≤15 s), adapts to multiple scenarios, verifies its engineering applicability and scalability in the dynamic scheduling of wafer manufacturing under strict JIT constraints, and provides a feasible solution for wafer manufacturing with high mix and strong temporal constraints.