Safdari Mohammad Javad, Mirjalili Seyed Mohammad, Bianucci Pablo, Zhang Xiupu
Appl Opt. 2018 Mar 10;57(8):1950-1957. doi: 10.1364/AO.57.001950.
In this paper, a novel framework for designing optimized photonic crystal (PhC) sensors has been proposed. The complexity of such structures has resulted in the lack of an analytical method to design the structures. Therefore, this framework aims to provide a comprehensive and automatic method to find the best values for the structural parameters without human involvement. The framework is explained with an example of designing a PhC liquid sensor. In the framework, an optimizer called the "multi-objective gray wolf optimizer" is utilized. However, a diverse range of multi-objective optimizer algorithms could be utilized. The results show that the proposed framework can design any kind of PhC sensor. Simplicity, being straightforward, and no human involvement are the advantages of the proposed framework. In addition, a significantly wide range of optimal designs will be found that are suitable for general and specific applications.
本文提出了一种用于设计优化光子晶体（PhC）传感器的新颖框架。此类结构的复杂性导致缺乏设计这些结构的解析方法。因此，该框架旨在提供一种全面且自动的方法，无需人工干预即可找到结构参数的最佳值。通过设计一个PhC液体传感器的示例对该框架进行了说明。在该框架中，使用了一种名为“多目标灰狼优化器”的优化器。然而，也可以使用各种不同的多目标优化器算法。结果表明，所提出的框架可以设计任何类型的PhC传感器。所提出框架的优点是简单、直接且无需人工干预。此外，还将找到适用于一般和特定应用的大量最优设计。
