遗传禁忌混合的膜系优化设计

Coating Optimization Design Using Genetic/Tabu Hybrid Optimization Algorithm

传统遗传算法的并行机制使得遗传算法的广域搜索能力较强,而禁忌搜索算法具有较快的收敛速度和较强的局部搜索能力。将遗传禁忌混合的优化算法用于光学薄膜的膜系优化设计中。混合优化算法的主体思路是以遗传算法为主体,把禁忌搜索算法的多样化特征引入遗传算法的交叉和变异中,从而使搜索过程具有记忆能力,实现两种算法的优势互补。通过减反膜和分束膜的实例优化设计,得到了比传统遗传算法更好的设计结果,表明该算法是高效和可靠的。

Traditional genetic algorithms （GA） are of good ability of global search because of its parallelism, while tabu search algorithm is of fast convergence and great local search capacity. Combining the advantages of genetic algorithms and tabu search algorithm, a new algorithm genetic/tabu hybrid optimization algorithm is proposed to design multilayer coatings. The theory of tabu search is imported into the crossover and mutation processes of GA, which makes the algorithm have the ability of memorizing. Better designs are obtained using genetic/tabu hybrid optimization algorithm to design antireflection coatings and beam splitter than the traditional GA. The results indicate the effectiveness and reliability of the algorithm.