Study of a topology optimization tool associating a hybrid algorithm with a Vorono&amp;#x00EF;-based formalism for the design of electromagnetic devices

Denies, Jonathan; Ahmed, Hamid Ben; Glineur, François; Dehez, Bruno

doi:10.1109/icelmach.2010.5607889

Cited by 2 publications

(2 citation statements)

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“…For TO a direct search method is usually used in symbiosis with a stochastic method thus defining hybrid algorithms. In such cases the deterministic method plays the role of local search, while the stochastic one is used for the global search [108], [136]. An example of flowchart of hybrid stochastic-deterministic algorithm can be seen in Fig.…”

Section: B Deterministic Methodsmentioning

confidence: 99%

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Topology Optimization for Electromagnetics: A Survey

et al. 2022

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The development of technologies for the additive manufacturing, in particular of metallic materials, is offering the possibility of producing parts with complex geometries. This opens up to the possibility of using topological optimization methods for the design of electromagnetic devices. Hence, a wide variety of approaches, originally developed for solid mechanics, have recently become attractive also in the field of electromagnetics. The general distinction between gradient-based and gradient-free methods drives the structure of the paper, with the latter becoming particularly attractive in the last years due to the concepts of artificial neural networks. The aim of this paper is twofold. On one hand, the paper aims at summarizing and describing the state-of-art on topology optimization techniques while on the other it aims at showing how the latter methodologies developed in non-electromagnetic framework (e.g., solid mechanics field) can be applied for the optimization of electromagnetic devices. Discussions and comparisons are both supported by theoretical aspects and numerical results.

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Section: B Deterministic Methodsmentioning

confidence: 99%

“…Schematic flowchart of TO using hybrid stochastic-deterministic method where Nc is the number of cells and Q1 the number of major cycles. Following[108], GA can be used as stochastic method and the deterministic Nelder-Mead for the local search.…”

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Topology Optimization for Electromagnetics: A Survey

et al. 2022

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Evolutionary Black-Box Topology Optimization: Challenges and Promises

Guirguis

Aulig

Picelli

et al. 2020

IEEE Trans. Evol. Computat.

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Black-box topology optimization (BBTO) uses evolutionary algorithms and other soft computing techniques to generate near-optimal topologies of mechanical structures. Although evolutionary algorithms are widely used to compensate the limited applicability of conventional gradient optimization techniques, methods based on BBTO have been criticized due to numerous drawbacks. In this paper, we discuss topology optimization as a black-box optimization problem. We review the main BBTO methods, discuss their challenges and present approaches to relax them. Dealing with those challenges effectively can lead to wider applicability of topology optimization, as well as the ability to tackle industrial, highly-constrained, nonlinear, many-objective and multimodal problems. Consequently, future research in this area may open the door for innovating new applications in science and engineering that may go beyond solving classical optimization problems of structural engineering. Furthermore, algorithms designed for BBTO can be added to existing software toolboxes and packages of topology optimization.

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Study of a topology optimization tool associating a hybrid algorithm with a Voronoï-based formalism for the design of electromagnetic devices

Cited by 2 publications

References 4 publications

Topology Optimization for Electromagnetics: A Survey

Topology Optimization for Electromagnetics: A Survey

Evolutionary Black-Box Topology Optimization: Challenges and Promises

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