Performance indicators in multiobjective optimization
In recent years, the development of new algorithms for multiobjective optimization has
considerably grown. A large number of performance indicators has been introduced to …
considerably grown. A large number of performance indicators has been introduced to …
Survey of multifidelity methods in uncertainty propagation, inference, and optimization
In many situations across computational science and engineering, multiple computational
models are available that describe a system of interest. These different models have varying …
models are available that describe a system of interest. These different models have varying …
Multi-objective bayesian optimization over high-dimensional search spaces
Many real world scientific and industrial applications require optimizing multiple competing
black-box objectives. When the objectives are expensive-to-evaluate, multi-objective …
black-box objectives. When the objectives are expensive-to-evaluate, multi-objective …
[KNIHA][B] Surrogate-model-based design and optimization
Surrogate-Model-Based Design and Optimization | SpringerLink Skip to main content
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Advertisement SpringerLink Account Menu Find a journal Publish with us Track your research …
Dual-surrogate-assisted cooperative particle swarm optimization for expensive multimodal problems
X Ji, Y Zhang, D Gong, X Sun - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Various real-world applications can be classified as expensive multimodal optimization
problems. When surrogate-assisted evolutionary algorithms (SAEAs) are employed to tackle …
problems. When surrogate-assisted evolutionary algorithms (SAEAs) are employed to tackle …
A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms
Evolutionary algorithms are widely used for solving multiobjective optimization problems but
are often criticized because of a large number of function evaluations needed …
are often criticized because of a large number of function evaluations needed …
Parallel surrogate-assisted global optimization with expensive functions–a survey
Surrogate assisted global optimization is gaining popularity. Similarly, modern advances in
computing power increasingly rely on parallelization rather than faster processors. This …
computing power increasingly rely on parallelization rather than faster processors. This …
Evolutionary multiobjective optimization: open research areas and some challenges lying ahead
Evolutionary multiobjective optimization has been a research area since the mid-1980s, and
has experienced a very significant activity in the last 20 years. However, and in spite of the …
has experienced a very significant activity in the last 20 years. However, and in spite of the …
A multiple surrogate assisted decomposition-based evolutionary algorithm for expensive multi/many-objective optimization
Many-objective optimization problems (MaOPs) contain four or more conflicting objectives to
be optimized. A number of efficient decomposition-based evolutionary algorithms have been …
be optimized. A number of efficient decomposition-based evolutionary algorithms have been …
Surrogate‐based methods for black‐box optimization
In this paper, we survey methods that are currently used in black‐box optimization, that is,
the kind of problems whose objective functions are very expensive to evaluate and no …
the kind of problems whose objective functions are very expensive to evaluate and no …