A Benchmark TEAM Problem for Multi-Objective Pareto Optimization of Electromagnetic Devices

Barba, Paolo Di; Mognaschi, Maria Evelina; Lowther, D.A.; Sykulski, J.K.

doi:10.1109/tmag.2017.2750901

Cited by 43 publications

(45 citation statements)

References 18 publications

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“…Nowadays, much effort is devoted to accelerate the numerical processes in optimization and inverse techniques in industrial and other domains. This example is aimed to solve a seemingly simple, benchmark problem, to find out an optimal distribution of current-carrying turns that should generate a homogeneous magnetic field in a given region [35]. The arrangement of the system is depicted in Fig.…”

Section: Team Benchmarkmentioning

confidence: 99%

Artap: Robust Design Optimization Framework for Engineering Applications

Pánek¹,

Orosz²,

Karban³

2019

2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS)

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The main goal of the Artap project is to provide an extensive infrastructure for robust design optimization, where usually many different numerical solvers have to be used together and the impact of the manufacturing uncertainties have to be minimized. Artap is an open-source software platform, developed jointly with the coupled numerical field solver, Agros-suite. Artap ensures interfaces for a broad collection of optimization algorithms (genetic and evolutionary algorithms, various interfaces to libraries such as Nlopt, Bayesopt, etc .), tools for machine learning (neural networks, Gaussian processes, etc. ), finite element solvers (Agros-suite, Comsol, Multiphysics, Deal.II). The implemented tools offers an easy and straightforward solution not only for robust design optimization but parameter identification, model order reduction, and shape optimization, as well. Moreover, Artap provides automatic parallelization of the optimization process. The paper presents the structure of the framework and technologies powering the project. The main features of Artap are demonstrated on an induction brazing process design tasks.

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Section: Team Benchmarkmentioning

confidence: 99%

Artap: Robust Design Optimization Framework for Engineering Applications

Pánek¹,

Orosz²,

Karban³

2019

2019 Third International Conference on Intelligent Computing in Data Sciences (ICDS)

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“…The results were good but the memory issue clearly visible. The hybrid kriging, with the burden of memory accumulation removed, has now been applied to the proposed new TEAM problem, with ten variables, details of which may be found in [11]. To summarize, an air-cored single-layer solenoid made up of 20 coils carries a certain current.…”

Section: Proposed Benchmark Teammentioning

confidence: 99%

Multi-Objective Pareto Optimization of Electromagnetic Devices Exploiting Kriging With Lipschitzian Optimized Expected Improvement

et al. 2018

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This paper focuses on resolving the storage issue of correlation matrices generated by kriging surrogate models in the context of electromagnetic optimization problems with many design variables and multiple objectives. The suggested-improved kriging approach incorporating a direct algorithm is able to maintain memory requirements at a nearly constant level while offering high efficiency of searching for a global optimum. The feasibility and efficiency of this proposed methodology are demonstrated using an example of a classic two-variable analytic function and a new proposed benchmark TEAM multi-objective Pareto optimization problem.

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“…This algorithm is able to solve single-objective problems (in this case it is called "ESTRA method" [16,17]) and multi-objective problems ("MOESTRA method" [18]). The search in the design space begins in a region of radius d0 (standard deviation) centered at the initial point m0 (mean value); m0 is externally provided, while d0 is internally calculated on the basis of the bounds boxing the variation of the design variables.…”

Section: Optimal Design Of An Electromagnetically Actuated Cantilevermentioning

confidence: 99%

Optimal design of electromagnetically actuated MEMS cantilevers

Barba¹,

Gotszalk²,

Majstrzyk³

et al. 2018

Preprint

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In this paper we present the numerical and experimental results of a design optimization of electromagnetic cantilevers. In particular, a cost-effective technique of evolutionary computing enabling the simultaneous minimization of multiple criteria is applied. A set of optimal solutions are subsequently fabricated and measured. The designed structures are fabricated in arrays, which makes the comparison and measurements of the sensor properties reliable. The microfabrication process, based on the silicon on insulator (SOI) technology, is proposed in order to minimize parasitic phenomena and enable efficient electromagnetic actuation. Measurements on the fabricated prototypes assessed the proposed methodological approach.

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A Benchmark TEAM Problem for Multi-Objective Pareto Optimization of Electromagnetic Devices

Cited by 43 publications

References 18 publications

Artap: Robust Design Optimization Framework for Engineering Applications

Artap: Robust Design Optimization Framework for Engineering Applications

Multi-Objective Pareto Optimization of Electromagnetic Devices Exploiting Kriging With Lipschitzian Optimized Expected Improvement

Optimal design of electromagnetically actuated MEMS cantilevers

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