Derivative-free optimization methods
In many optimization problems arising from scientific, engineering and artificial intelligence
applications, objective and constraint functions are available only as the output of a black …
applications, objective and constraint functions are available only as the output of a black …
Inflatable origami: Multimodal deformation via multistability
Inflatable structures have become essential components in the design of soft robots and
deployable systems as they enable dramatic shape change from a single pressure inlet …
deployable systems as they enable dramatic shape change from a single pressure inlet …
Review and comparison of algorithms and software for mixed-integer derivative-free optimization
This paper reviews the literature on algorithms for solving bound-constrained mixed-integer
derivative-free optimization problems and presents a systematic comparison of available …
derivative-free optimization problems and presents a systematic comparison of available …
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 …
Multi objective optimization of computationally expensive multi-modal functions with RBF surrogates and multi-rule selection
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 …
objective optimization that is designed to obtain good non-dominated solutions to black box …
Surrogate optimization of deep neural networks for groundwater predictions
Sustainable management of groundwater resources under changing climatic conditions
require an application of reliable and accurate predictions of groundwater levels …
require an application of reliable and accurate predictions of groundwater levels …
Surrogate-assisted grey wolf optimization for high-dimensional, computationally expensive black-box problems
In this paper, a Surrogate-Assisted Grey Wolf Optimization (SAGWO) algorithm for high-
dimensional and computationally expensive problems is presented, where Radial Basis …
dimensional and computationally expensive problems is presented, where Radial Basis …
Kriging-assisted teaching-learning-based optimization (KTLBO) to solve computationally expensive constrained problems
H Dong, P Wang, C Fu, B Song - Information Sciences, 2021 - Elsevier
In this paper, a novel algorithm KTLBO is presented to achieve computationally expensive
constrained optimization. In KTLBO, Kriging is adopted to develop dynamically updated …
constrained optimization. In KTLBO, Kriging is adopted to develop dynamically updated …
Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems
Q Gu, Q Wang, NN **ong, S Jiang, L Chen - Complex & Intelligent Systems, 2022 - Springer
Surrogate-assisted optimization has attracted much attention due to its superiority in solving
expensive optimization problems. However, relatively little work has been dedicated to …
expensive optimization problems. However, relatively little work has been dedicated to …
SOCEMO: surrogate optimization of computationally expensive multiobjective problems
J Müller - INFORMS Journal on Computing, 2017 - pubsonline.informs.org
We present the algorithm SOCEMO for optimization problems that have multiple conflicting
computationally expensive black-box objective functions. The computational expense …
computationally expensive black-box objective functions. The computational expense …