Many problems in real life can be seen as Expensive Optimization Problems (EOPs).
Compared with traditional optimization problems, the evaluation cost of candidate solutions …

Evolutionary computation is a rapidly evolving field and the related algorithms have been
successfully used to solve various real-world optimization problems. The past decade has …

Surrogate-assisted evolutionary algorithms (EAs) have been intensively used to solve
computationally expensive problems with some success. However, traditional EAs are not …

Abstract Particle Swarm Optimization (PSO) is a well-known and powerful meta-heuristic
algorithm in Swarm Intelligence (SI), and it was invented by simulating the foraging behavior …

Initialization of metaheuristics is a crucial topic that lacks a comprehensive and systematic
review of the state of the art. Providing such a review requires in‐depth study and …

Various real-world applications can be classified as expensive multimodal optimization
problems. When surrogate-assisted evolutionary algorithms (SAEAs) are employed to tackle …

The radial basis function (RBF) model and the Kriging model have been widely used in the
surrogate-assisted evolutionary algorithms (SAEAs). Based on their characteristics, a global …

This article presents a surrogate-assisted multiswarm optimization (SAMSO) algorithm for
high-dimensional computationally expensive problems. The proposed algorithm includes …

Abstract Stochastic Fractal Search (SFS) is a new and original meta-heuristic search (MHS)
algorithm with strong foundations. As with many other MHS methods, there are problems in …

Many real-world applications can be formulated as expensive multimodal optimization
problems (EMMOPs). When surrogate-assisted evolutionary algorithms (SAEAs) are …