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A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
Integrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
Rapid design of miniaturised branch-line couplers through concurrent cell optimisation and surrogate-assisted fine-tuning
In this study, the authors introduce a methodology for low-cost simulation-driven design optimisation of highly miniaturised branch-line couplers (BLCs). The first stage of their design approach exploits fast concurrent optimisation of geometrically dependent, but electromagnetically isolated cells that constitute a BLC. The cross-coupling effects between the cells are taken into account in the second stage, where a surrogate-assisted...
Fast EM-driven size reduction of antenna structures by means of adjoint sensitivities and trust regions
In this letter, a simple yet robust and computationally efficient optimization technique for explicit size reduction of antenna structures is presented. Our approach directly handles the antenna size as the main design objective, while ensuring satisfactory electrical performance by means of suitably defined penalty functions. For the sake of accuracy, the antenna structure is evaluated using high-fidelity EM simulation. In order...
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