A radial basis function surrogate model assisted evolutionary algorithm for high-dimensional expensive optimization problems
Evolutionary algorithms require large number of function evaluations to locate the global
optimum, making it computationally prohibitive on dealing with expensive problems …
optimum, making it computationally prohibitive on dealing with expensive problems …
A novel evolutionary sampling assisted optimization method for high-dimensional expensive problems
X Wang, GG Wang, B Song, P Wang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Surrogate-assisted evolutionary algorithms (SAEAs) are promising methods for solving high-
dimensional expensive problems. The basic idea of SAEAs is the integration of nature …
dimensional expensive problems. The basic idea of SAEAs is the integration of nature …
A sequential constraints updating approach for Kriging surrogate model-assisted engineering optimization design problem
Kriging surrogate model has been widely used in engineering design optimization problems
to replace computational cost simulations. To facilitate the usage of the Kriging surrogate …
to replace computational cost simulations. To facilitate the usage of the Kriging surrogate …
Efficient hierarchical surrogate-assisted differential evolution for high-dimensional expensive optimization
Surrogate-assisted evolutionary algorithms have gained increasingly attention due to the
promising search capabilities for solving computationally expensive optimization problems …
promising search capabilities for solving computationally expensive optimization problems …
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 …
Optimal energy management with balanced fuel economy and battery life for large hybrid electric mining truck
With the addition of an energy storage system (ESS) and advanced controls, a hybrid
electric propulsion system can considerably improve the fuel economy over a pure …
electric propulsion system can considerably improve the fuel economy over a pure …
Surrogate-assisted teaching-learning-based optimization for high-dimensional and computationally expensive problems
H Dong, P Wang, X Yu, B Song - Applied Soft Computing, 2021 - Elsevier
In this work, a surrogate-assisted teaching-learning-based optimization algorithm is
presented for high-dimensional and computationally expensive black-box optimization …
presented for high-dimensional and computationally expensive black-box optimization …
Optimal energy management strategy of fuel‐cell battery hybrid electric mining truck to achieve minimum lifecycle operation costs
Proton exchange membrane fuel cell (PEMFC) electric vehicle is an effective solution for
improving fuel efficiency and onboard emissions, taking advantage of the high energy …
improving fuel efficiency and onboard emissions, taking advantage of the high energy …
SCGOSR: Surrogate-based constrained global optimization using space reduction
Global optimization problems with computationally expensive objective and constraints are
challenging. In this work, we present a new kriging-based constrained global optimization …
challenging. In this work, we present a new kriging-based constrained global optimization …