Wang Yingzhi, Han Tailin, Jiang Xu, Yan Yuhan, Liu Hong
School of Electronics and Information Engineering, Changchun University of Science and Technology, Changchun 130022, China.
School of Opto-electronic Engineering, Changchun University of Science and Technology, Changchun 130022, China.
Entropy (Basel). 2020 Mar 3;22(3):295. doi: 10.3390/e22030295.
In the process of digital micromirror device (DMD) digital mask projection lithography, the lithography efficiency will be enhanced greatly by path planning of pattern transfer. This paper proposes a new dual operator and dual population ant colony (DODPACO) algorithm. Firstly, load operators and feedback operators are used to update the local and global pheromones in the white ant colony, and the feedback operator is used in the yellow ant colony. The concept of information entropy is used to regulate the number of yellow and white ant colonies adaptively. Secondly, take eight groups of large-scale data in TSPLIB as examples to compare with two classical ACO and six improved ACO algorithms; the results show that the DODPACO algorithm is superior in solving large-scale events in terms of solution quality and convergence speed. Thirdly, take PCB production as an example to verify the time saved after path planning; the DODPACO algorithm is used for path planning, which saves 34.3% of time compared with no path planning, and is about 1% shorter than the suboptimal algorithm. The DODPACO algorithm is applicable to the path planning of pattern transfer in DMD digital mask projection lithography and other digital mask lithography.
在数字微镜器件（DMD）数字掩膜投影光刻过程中，通过图案转移的路径规划可大幅提高光刻效率。本文提出了一种新型的双算子双种群蚁群（DODPACO）算法。首先，在白蚁群中使用加载算子和反馈算子来更新局部和全局信息素，在黄蚁群中使用反馈算子。利用信息熵的概念自适应地调节黄蚁群和白蚁群的数量。其次，以TSPLIB中的八组大规模数据为例，与两种经典蚁群算法和六种改进蚁群算法进行比较；结果表明，DODPACO算法在解决大规模问题时，在解的质量和收敛速度方面具有优势。第三，以印刷电路板（PCB）生产为例，验证路径规划后节省的时间；采用DODPACO算法进行路径规划，与无路径规划相比节省了34.3%的时间，比次优算法短约1%。DODPACO算法适用于DMD数字掩膜投影光刻及其他数字掩膜光刻中的图案转移路径规划。
