Surrogate model assisted optimization of the PFT
A Parallel Surrogate Model Assisted Evolutionary Algorithm for Electromagnetic Design Optimization
... Although DE/rand/1 and DE/rand/2 are several times slower than the mutation strategies in the fast convergence cluster under the standard SMAS framework, it may not necessarily slow down the convergence when introducing ...
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Comparison of Parallel Surrogate-Assisted Optimization Approaches
... second model with a largely reduced amount of cells in the simulation mesh was ...the model was reduced to only a few seconds per ...reduced model still captures some of the difficulties and complex ...
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Surrogate-assisted multiobjective optimization based on decomposition
... the model is of high importance, not only to reduce the amount of data for accelerating the training phase, but also to improve solution ...computationally-demanding model training tasks, this also enables ...
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Global Optimization of Microwave Filters Based on a Surrogate Model Assisted Evolutionary Algorithm
... filter optimization problems which are difficult to be solved by popular local optimization methods, while at the same time are not affordable to be solved by standard global optimization methods, so ...
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Global optimization of microwave filters based on a surrogate model-assisted evolutionary algorithm
... global surrogate model and then iteratively improve the solution quality and the surrogate model quality in the consecutive ...filter optimization, much of this computing overhead is ...
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Efficient global optimization of actuator based on a surrogate model assisted hybrid algorithm
... Global Optimization of Actuator Based on A Surrogate Model Assisted Hybrid Algorithm Bo Liu, Senior Member, IEEE, Vic Grout, Senior Member, IEEE, Anna Nikolaeva Abstract—Computationally ...
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Efficient Global Optimization of Actuator Based on A Surrogate Model Assisted Hybrid Algorithm
... Global Optimization of Actuator Based on A Surrogate Model Assisted Hybrid Algorithm Bo Liu, Senior Member, IEEE, Vic Grout, Senior Member, IEEE, Anna Nikolaeva Abstract—Computationally ...
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A multi-fidelity surrogate-model-assisted evolutionary algorithm for computationally expensive optimization problems
... data-driven surrogate models and simulation models of dierent ac- curacies (or delities) in a single algorithm to address computationally expen- sive global optimization problems has recently attracted ...
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Combinatorial Surrogate-Assisted Optimization for Bus Stops Spacing Problem
... combinatorial surrogate models to approximate the costly traffic ...fresh surrogate-assisted optimiza- tion algorithm based on the mathematical foundations of discrete Walsh functions in order to ...
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Parallel surrogate-assisted global optimization with expensive functions – a survey
... Abstract Surrogate assisted global optimization is gaining ...in surrogate based global optimi- ...to optimization based on adaptive sampling, surro- gate assisted parallel ...
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Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies
... 4.2 Experimental results In Figure 1, the median attainment surfaces of the cm-OneMax problem are shown for high and low correlations and latency values. On the top row, the correlation is -0.5 between the objectives ...
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Hierarchical surrogate-assisted evolutionary multi-scenario airfoil shape optimization
... shape optimization prob- lems, an evaluation of a single airfoil is based on its full-scenario drag ...shape optimization will be computationally highly intensive. Although surrogate-assisted ...
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An adaptive evolution control based on confident regions for surrogate-assisted optimization
... The fitness function evaluation requires a system of nonlinear partial differential equations reflecting both water flow and chemical reactions to be treated and takes up to 4 minutes. In [1], a MO strategy based on an ...
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Intensive Surrogate Model Exploitation in Self-adaptive Surrogate-assisted CMA-ES (saACM-ES)
... for surrogate model ex- ploitation, where a larger population size is used to optimize the surrogate, while the default population size is used to op- timize the expensive ...the surrogate is ...
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Intensive surrogate model exploitation in self-adaptive surrogate-assisted cma-es (saacm-es)
... for surrogate model ex- ploitation, where a larger population size is used to optimize the surrogate, while the default population size is used to op- timize the expensive ...the surrogate is ...
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Proper orthogonal decomposition as surrogate model for aerodynamic optimization
... A surrogate model based on the proper orthogonal decomposition is developed in order to enable fast and reliable evaluations of aerodynamic ...the surrogate model is constructed in the (Mach, ...
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Data-Driven Surrogate-Assisted Multi-Objective Evolutionary Optimization of A Trauma System
... Data-Driven Surrogate-Assisted Multi-Objective Evolutionary Optimization of A Trauma System Handing Wang, Member, IEEE, Yaochu Jin, Fellow, IEEE, Jan ...evolutionary optimization assumes that ...
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A Classification Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization
... expensive optimization prob- lems where only a small number of real fitness evaluations are ...existing surrogate-assisted evolutionary algo- rithms are designed for solving low-dimensional single or ...
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Surrogate-assisted reliability-based design optimization: a survey and a new general framework
... 3.2 Use of advanced techniques and simulation in RBDO The three groups of methods introduced in the previous section rely on approximation meth- ods for computing failure probabilities. The numerous contributions all ...
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Variable Fidelity Surrogate Assisted Optimization Using A Suite of Low Fidelity Solvers
... Variable-fidelity optimization (VFO) has emerged as an attractive method of performing, both, high-speed and high- fidelity ...a surrogate to ac- count for the difference between the high- and low-fidelity ...
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