微奈米週期結構展現了調變光學與熱輻射性質的能力，而被應用各式元件的開發，而由於應用所須的頻譜特性大相逕庭，如何進行有效率的設計為一重要的課題。進化式演算法與群體智能方法近年來被廣為發展及大量運用於工程最佳化上，並已獲致諸多良好成果，故本研究主題在結合嚴格耦合波分析理論與數種具隨機性之最佳化方法，對滿足特殊輻射性質之微奈米週期結構進行外型及尺寸的設計。應用一為本文提出之光學密碼系統，因週期結構光學性質為極複雜之多參數函數，提供了密碼系統所須之安全性。而其中結構尺寸等參數被運用為解密的關鍵資訊，則以基因演算法與另一混成式最佳化方法獲得。應用二為窄頻及寬頻之波長選擇性熱放射器，係調變週期結構於紅外光頻譜的輻射性質。此處光柵形貌與尺寸的最佳化則運用了差值進化法，甚至加入一種使用微小族群的技巧以在高參數維度的問題上進一步增加搜尋效率。

Micro/Nanoscale periodic structures are promising for tailoring optical and thermal properties for various applications. Since their expected spectrum differ greatly with applications, an efficient way of design is important. Evolutionary algorithms and methods with swarm intelligence have been developed and applied on wide engineering optimization problems. However, the way to employ them efficiently on various problems is still critical. In this work, the rigorous coupled-wave analysis and several stochastic optimization methods are integrated to design the profiles of period structures for specific radiative properties. Firstly, optical cryptographic schemes will be proposed. The optical responses of periodic structures provide the desired complexity of cryptosystems to achieve security. In which the geometric parameters can be applied as keys to messages, and they were obtained with genetic algorithms and a hybrid method. Another investigated application is selective thermal emitters with narrow/wide bandwidth for the potential of surface gratings on manipulating infrared emission. The differential evolution method was applied to optimize the profile of gratings. Moreover, a micro- operator will be suggested for high-dimensional problems for enhancing search efficiency.

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