Global optimal reliability index of implicit composite laminate structures by evolutionary algorithms - das Neves Carneiro, Gonçalo; Conceição António, Carlos (Structural safety, 2019)
•Solving the Reliability Index Approach (RIA) by evolutionary algorithms (EAs).•A hybrid genetic algorithm searches the global most probable failure point (MPP).•New evolutionary operators: genetic repair and reduction/reallocation of the search domain.•Implicit analysis of laminated composite structures with multivariate uncertainty space.•Comparison with gradient-based algorithm and Monte Carlo simulation. With uncertainty, reliability assessment is fundamental in structural optimization, because optimization itself is often against safety. To avoid Monte Carlo methods, the Reliability Index Approach (RIA) approximates the structural failure probability and is formulated as a minimization problem, usually solved with fast gradient-methods, at the expense of local convergence, or even divergence, particularly for highly dimensional problems and implicit physical models. In this paper, a new procedure for global convergence of the RIA, with practical efficiency, is presented. Two novel evolutionary operators and a mixed real-binary genotype, suitable to hybridize any Evolutionary Algorithm with elitist strategy, are developed. As an example, a shell laminate structure is presented and the results validated, showing good convergence and efficiency. The proposed method is expected to set the basis for further developments on the design optimization of more complex structures with multiple failure criteria.