Structural reliability assessment by salp swarm algorithm–based FORM

Abstract The first‐order reliability method (FORM) is well recognized as an efficient approach for reliability analysis. Rooted in considering the reliability problem as a constrained optimization of a function, the traditional FORM makes use of gradient‐based optimization techniques to solve it. However, the gradient‐based optimization techniques may result in local convergence or even divergence for the highly nonlinear or high‐dimensional performance function. In this paper, a hybrid method combining the Salp Swarm Algorithm (SSA) and FORM is presented. In the proposed method, a Lagrangian objective function is constructed by the exterior penalty function method to facilitate meta‐heuristic optimization strategies. Then, SSA with strong global optimization ability for highly nonlinear and high‐dimensional problems is utilized to solve the Lagrangian objective function. In this regard, the proposed SSA‐FORM is able to overcome the limitations of FORM including local convergence and divergence. Finally, the accuracy and efficiency of the proposed SSA‐FORM are compared with two gradient‐based FORMs and several heuristic‐based FORMs through eight numerical examples. The results show that the proposed SSA‐FORM can be generally applied for reliability analysis involving low‐dimensional, high‐dimensional, and implicit performance functions.