Structural engineering is focused on the safe and efficient design of infrastructure. Projects can range in size and complexity, many requiring massive amounts of materials and expensive construction and operational costs. Therefore, one of the primary objectives for structural engineers is a cost-effective design. Incorporating optimality criteria into the design procedure introduces additional complexities that result in problems that are nonlinear, nonconvex, and have a discontinuous solution space. Population-based optimization algorithms (known as metaheuristics) have been found to be very efficient approaches to these problems. Many researchers have developed and applied state-of-art metaheuristics to automate and optimize the design of real-world civil engineering problems. While there is a large body of published papers in this area, there are few comprehensive reviews that list, summarize, and categorize metaheuristic optimization in structural engineering. This paper provides an extensive survey of a wide range of metaheuristic techniques to structural engineering optimization problems. Also, information is provided on available structural engineering benchmark problems, the formulation of different objective functions, and the handling of various types of constraints. The performance of different optimization techniques is compared for many benchmark problems.

结构工程专注于基础设施的安全和高效设计。项目的规模和复杂性各不相同，许多项目需要大量材料以及昂贵的建设和运营成本。因此，结构工程师的主要目标之一是具有成本效益的设计。将最优性标准纳入设计过程会引入额外的复杂性，从而导致非线性、非凸和具有不连续解空间的问题。已经发现基于群体的优化算法（称为元启发式）是解决这些问题的非常有效的方法。许多研究人员已经开发并应用了最先进的元启发式方法来自动化和优化现实世界土木工程问题的设计。虽然在这个领域有大量已发表的论文，很少有综合评论列出、总结和分类结构工程中的元启发式优化。本文对结构工程优化问题的各种元启发式技术进行了广泛的调查。此外，还提供了有关可用结构工程基准问题、不同目标函数的制定以及各种类型约束处理的信息。针对许多基准问题比较了不同优化技术的性能。提供有关可用结构工程基准问题、不同目标函数的制定以及各种类型约束处理的信息。针对许多基准问题比较了不同优化技术的性能。提供有关可用结构工程基准问题、不同目标函数的制定以及各种类型约束处理的信息。针对许多基准问题比较了不同优化技术的性能。