Bayes approach to solving T.E.A.M. benchmark problems 22 and 25 and its comparison with other optimization techniques

Karban, Pavel; Kropík, Petr; Kotlan, Václav; Doležel, Ivo

doi:10.1016/j.amc.2017.07.043

Cited by 10 publications

(1 citation statement)

References 20 publications

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“…Consequently, the best configuration among all runs analysed in this paper is run 18. Finally, to validate the proposed VEM approach, in Table 3, we compare the design variables obtained with this approach and the ones coming from a standard FEM analysis and other optimisation processes [20,21]. From these data, we observe that the best design variables obtained by this procedure are in accordance with the ones in the literature.…”

Section: Optimisation Resultsmentioning

confidence: 58%

Curved Domains in Magnetics: A Virtual Element Method Approach for the T.E.A.M. 25 Benchmark Problem

Dassi,

Di Barba,

Russo

2024

Electronics

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In this paper, we are interested in solving optimal shape design problems. A critical challenge within this framework is generating the mesh of the computational domain at each optimisation step according to the information provided by the minimising functional. To enhance efficiency, we propose a strategy based on the Finite Element Method (FEM) and the Virtual Element Method (VEM). Specifically, we exploit the flexibility of the VEM in dealing with generally shaped polygons, including those with hanging nodes, to update the mesh solely in regions where the shape varies. In the remaining parts of the domain, we employ the FEM, known for its robustness and applicability in such scenarios. We numerically validate the proposed approach on the T.E.A.M. 25 benchmark problem and compare the results obtained with this procedure with those proposed in the literature based solely on the FEM. Moreover, since the T.E.A.M. 25 benchmark problem is also characterised by curved shapes, we utilise the VEM to accurately incorporate these “exact” curves into the discrete solution itself.

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Section: Optimisation Resultsmentioning

confidence: 58%

Curved Domains in Magnetics: A Virtual Element Method Approach for the T.E.A.M. 25 Benchmark Problem

Dassi,

Di Barba,

Russo

2024

Electronics

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A survey of the state-of-the-art swarm intelligence techniques and their application to an inverse design problem

Khan

Ling

2020

J Comput Electron

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This paper encompasses a detailed review of state-of-the-art swarm-based algorithms with a focus on their applications along with a discussion on the merits and limitations of each algorithm. Further, a recently developed Advanced Particle Swarm Optimization (APSO) algorithm was compared with the different state-of-the-art-swarmbased algorithms through solving an electromagnetic inverse problem. Results showed that the APSO algorithm has outperformed the other algorithms. This research provides a scientific guideline for the comparison of different swarmbased algorithms and their utilization regarding specific applications.

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Methodology of determining material parameters based on optimization techniques

Petrasova

Kotlan

Pánek

et al. 2021

Journal of Computational and Applied Mathematics

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Bayes approach to solving T.E.A.M. benchmark problems 22 and 25 and its comparison with other optimization techniques

Cited by 10 publications

References 20 publications

Curved Domains in Magnetics: A Virtual Element Method Approach for the T.E.A.M. 25 Benchmark Problem

Curved Domains in Magnetics: A Virtual Element Method Approach for the T.E.A.M. 25 Benchmark Problem

A survey of the state-of-the-art swarm intelligence techniques and their application to an inverse design problem

Methodology of determining material parameters based on optimization techniques

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