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作 者:张朋[1] 张洁[1] 王卓君 孙可芯 ZHANG Peng;ZHANG Jie;WANG Zhuojun;SUN Kexin(Institute of Artificial Intelligence,Donghua University,Shanghai 201620,Chin;College of Mechanical Engineering,Donghua University,Shanghai 201620,China)
机构地区:[1]东华大学人工智能研究院,上海201620 [2]东华大学机械工程学院,上海201620
出 处:《华中科技大学学报(自然科学版)》2022年第4期26-32,共7页Journal of Huazhong University of Science and Technology(Natural Science Edition)
基 金:国家自然科学基金资助项目(52005099);中央高校基本科研业务费专项资金资助项目(223202100044).
摘 要:针对晶圆制造系统光刻区调度问题,考虑设备专用性约束、掩膜版数量约束及设备加工能力约束,以最小化总完工时间和光刻成本、最大化晶圆准时交付率和设备利用率为目标,提出了基于分解多目标进化算法的光刻区调度方法.针对非支配前沿点分布不均的问题,设计了基于聚类分析的参考点生成方法;综合考虑非支配解的分布均匀性、收敛性及计算资源的合理分配,改进了惩罚边界交叉聚合函数;设计了外部档案变邻域搜索方法,提高算法的求解质量和收敛速度.24组基准算例和晶圆制造仿真系统连续12个月的测试结果表明:提出的分解多目标进化算法相对于多种多目标进化算法,能够取得更好的收敛性和解的多样性.A decomposition multi-objective evolutionary algorithm based photolithography area scheduling method was proposed for photolithography area scheduling problem in wafer fabrication system with the consideration of dedicated machine constraints,mask quantity constraints and equipment processing capacity constraints,and the objective was to minimize total completion time and cost of photolithography and maximize wafer on-time delivery and equipment utilization simultaneously.A clustering based reference points generation method was presented to deal with the uneven distribution of non-dominated frontier points.The penalty-based boundary cross aggregation function was improved to balance solution distribution,convergence and computing resources allocation.Besides,a variable neighborhood search method for external files was designed to improve the solution quality and convergence speed.Results from 24 benchmark instances and 12 consecutive months running of a wafer fabrication simulation system show that the proposed decomposition multi-objective evolutionary algorithm has better convergence and solution diversity than several multi-objective evolutionary algorithms.
关 键 词:晶圆制造系统 光刻区 多目标调度 分解多目标进化算法 聚合函数
分 类 号:TH166[机械工程—机械制造及自动化]
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