基于精英选择自适应变异遗传算法的膜系优化设计

将改进的遗传算法——精英选择自适应变异遗传算法(EGAAM)用于光学薄膜的膜系优化设计。EGAAM采用了独特的自适应变异操作,该操作既使得群体保持了多样性,防止过早收敛,又加快了群体收敛速度。EGGAM对初始条件不敏感,并且可以确定膜层厚度边界,确保了设计结果的制备方便。通过减反膜、分光膜的实例优化设计表明,在相同设计条件下,用EGAAM可以得到比传统遗传算法更好的设计结果。理论与实例表明EGAAM用于膜系优化设计是高效和可靠的。

Coating optimization design based on elite genetic algorithm with adaptive mutations

A modified genetic algorithm,elite genetic algorithm with adaptive mutations(EGAAM),was applied to optical coating optimization design.Adaptive mutation which maintains the diversity of population,preventing premature convergence and quickening the convergence speed of population,is employed in EGAAM.The result shows the EGAAM can get the design of better performance than GA algorithm under the same design conditions through the optimization examples of antireflection film and splitting film.The EGAAM is not sensitive to the initial condition and the boundary of the coating can be predetermined,so it is convenient to fabricate the results of design.Theoretical and practical examples show that the EGAAM is highly effective and reliable in coating optimization design.