Expected improvement for expensive optimization: a review
The expected improvement (EI) algorithm is a very popular method for expensive
optimization problems. In the past twenty years, the EI criterion has been extended to deal …
optimization problems. In the past twenty years, the EI criterion has been extended to deal …
Surrogate modeling: tricks that endured the test of time and some recent developments
Tasks such as analysis, design optimization, and uncertainty quantification can be
computationally expensive. Surrogate modeling is often the tool of choice for reducing the …
computationally expensive. Surrogate modeling is often the tool of choice for reducing the …
Multiple penalties and multiple local surrogates for expensive constrained optimization
This article proposes an evolutionary algorithm using multiple penalties and multiple local
surrogates (MPMLS) for expensive constrained optimization. In each generation, MPMLS …
surrogates (MPMLS) for expensive constrained optimization. In each generation, MPMLS …
A surrogate-assisted differential evolution with knowledge transfer for expensive incremental optimization problems
In some real-world applications, the optimization problems may involve multiple design
stages. At each design stage, the objective is incrementally modified by incorporating more …
stages. At each design stage, the objective is incrementally modified by incorporating more …
[HTML][HTML] Efficient reliability analysis based on adaptive sequential sampling design and cross-validation
NC Xiao, MJ Zuo, W Guo - Applied Mathematical Modelling, 2018 - Elsevier
Surrogate-models have proven to be an effective strategy for structural systems with
expensive-to-evaluate simulations and are very useful for structural reliability analysis. Many …
expensive-to-evaluate simulations and are very useful for structural reliability analysis. Many …
A general framework of surrogate-assisted evolutionary algorithms for solving computationally expensive constrained optimization problems
The objective and constraints of expensive constrained optimization problems (ECOPs) are
often evaluated using simulations with different computational costs. However, the existing …
often evaluated using simulations with different computational costs. However, the existing …
Self-adjusting parameter control for surrogate-assisted constrained optimization under limited budgets
Constrained optimization of high-dimensional numerical problems plays an important role in
many scientific and industrial applications. Function evaluations in many industrial …
many scientific and industrial applications. Function evaluations in many industrial …
Efficient global optimization of constrained mixed variable problems
Due to the increasing demand for high performance and cost reduction within the framework
of complex system design, numerical optimization of computationally costly problems is an …
of complex system design, numerical optimization of computationally costly problems is an …
A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization
Expected improvement (EI) is a popular infill criterion in Gaussian process assisted
optimization of expensive problems for determining which candidate solution is to be …
optimization of expensive problems for determining which candidate solution is to be …
An efficient constrained global optimization algorithm with a clustering-assisted multiobjective infill criterion using Gaussian process regression for expensive …
P Jiang, Y Cheng, J Yi, J Liu - Information Sciences, 2021 - Elsevier
Constrained optimization problems trouble engineers and researchers because of their high
complexity and computational cost. When the objective function and constraints are both …
complexity and computational cost. When the objective function and constraints are both …