Surrogate assisted global optimization is gaining popularity. Similarly, modern advances in
computing power increasingly rely on parallelization rather than faster processors. This …

This paper reviews the existing literature on the combination of metaheuristics with machine
learning methods and then introduces the concept of learnheuristics, a novel type of hybrid …

GOMORS is a parallel response surface-assisted evolutionary algorithm approach to multi-
objective optimization that is designed to obtain good non-dominated solutions to black box …

In this article, grey-box and black-box surrogate modeling are described, with some key
findings. The important point is that surrogate modeling has a solid mathematical basis …

Contemporary real-world optimization benchmarks are subject to many constraints and are
often high-dimensional problems. Typically, such problems are expensive in terms of …

Optimization algorithms and urban inundation models are powerful tools to identify cost‐
effective designs of urban green infrastructures such as low‐impact developments (LIDs) …

Although researchers have successfully incorporated metamodels in evolutionary
algorithms to solve computational-expensive optimization problems, they have scarcely …

Surrogate-assisted multi-objective evolutionary algorithms have become increasingly
popular for solving computationally expensive problems, profiting from surrogate modeling …

To relieve the computational cost of design evaluations using expensive finite element (FE)
simulations, surrogate models have been widely applied in computer-aided engineering …

Aiming for a sustainable building stock, air-source heat pump systems are a key technology.
In residential application, heat pump systems typically consist of a heat pump, an auxiliary …