A new framework for reliability-based design optimization using metaheuristic algorithms

Abstract

This paper presents a new framework for reliability-based design optimization (RBDO) using metaheuristic algorithms based on decoupled methods. The sequential optimization and reliability assessment (SORA) is utilized as a decoupled method in this study. In the present framework, unlike the previous RBDO based on decoupled methods, a metaheuristic is employed on both reliability assessment and the optimization parts. Here, first a new reliability assessment method based on the metaheuristics is introduced. Then, a new termination condition for the metaheuristic inspired by the termination condition of the gradient-based method is presented. In order to investigate the efficiency of the proposed framework, an enhanced shuffled shepherd optimization algorithm (ESSOA) is used as an optimization approach. The efficiency of the proposed framework is evaluated by four well-known RBDO benchmarks investigated in the previous studies using the gradient-based method. Also, the two new RBDO problems are introduced in this study. The results show that the proposed framework can have better performance than the gradient-based method in the RBDO and can easily be utilized in a wide range of RBDO problems.