In this paper, an Enhanced Forensic-Based Investigation (EFBI) is proposed for optimal design of frequency-constrained dome-like trusses. The Forensic-Based Investigation (FBI) algorithm is a newly developed population-based metaheuristic inspired by the criminal investigation process. Throughout the FBI algorithm, the investigation and pursuit teams (i.e., the diversification and the intensification components of FBI, respectively) cooperate with each other to solve the target optimization problem. This study aims to modify the original formulation of FBI and propose an enhanced version of FBI, named as EFBI. The proposed EFBI seeks to reinforce communication between the investigation and pursuit teams with the aim of striking a better balance between the intensification and the diversification tasks. The performance of the proposed EFBI is compared with those of the standard FBI and some other optimization methods through three well-studied dome truss optimization problems with frequency constraints. To the best of our knowledge, this is the first time that FBI is applied to structural optimization. Results confirm that EFBI significantly outperforms the standard FBI, and has superior or comparable performance to other considered metaheuristics.

在本文中，提出了一种基于增强取证的调查 (EFBI)，用于优化设计频率受限的圆顶状桁架。基于法医的调查 (FBI) 算法是一种受刑事调查过程启发而新开发的基于人口的元启发式算法。在整个 FBI 算法中，调查组和追击组（即分别是 FBI 的多元化和集约化组件）相互配合，解决目标优化问题。本研究旨在修改FBI的原始表述，并提出FBI的增强版本，命名为EFBI。拟议的 EFBI 旨在加强调查和追捕小组之间的沟通，目的是在强化和多样化任务之间取得更好的平衡。通过三个经过充分研究的具有频率约束的圆顶桁架优化问题，将所提出的 EFBI 的性能与标准 FBI 和其他一些优化方法的性能进行了比较。据我们所知，这是首次将 FBI 应用于结构优化。结果证实，EFBI 显着优于标准 FBI，并且与其他考虑的元启发式算法相比具有优越或可比的性能。