The design of complex aerospace systems is a multidisciplinary design optimization (MDO)
problem involving the interaction of multiple disciplines. However, because of the necessity …

Abstract Surrogate-Assisted Evolutionary Optimisation algorithms are a specialized brand of
optimisers developed to undertake problems with computationally expensive fitness …

Evolutionary algorithms require large number of function evaluations to locate the global
optimum, making it computationally prohibitive on dealing with expensive problems …

Surrogate-assisted evolutionary algorithms (SAEAs) are promising methods for solving high-
dimensional expensive problems. The basic idea of SAEAs is the integration of nature …

Engineering optimization problems usually involve computationally expensive simulations
and massive design variables. Solving these problems in an efficient manner is still a big …

Multiple surrogates can be trained in surrogate-assisted optimization of expensive problems
to describe different characteristics of the real fitness landscape. It has been shown that …

This paper presents a vibration‐based model updating procedure for historical masonry
structures which have suffered severe damage due to seismic events. This allows gathering …

Evolutionary algorithm provides a powerful tool to the solution of modern complex
engineering optimization problems. In general, a great deal of evaluation effort often …

Many fitness evaluations are often needed for large-scale evolutionary optimization to find
the optimal solution. Therefore, evolutionary algorithms are impeded to solve …

Surrogate-assisted evolutionary algorithms (SAEAs) are promising methods for addressing
computationally expensive problems. This paper proposes a multiple surrogates and …