Adapted Output Space-Mapping Technique for a Bi-Objective Optimization

Tran, Trung-Viet; Moussouni, Fouzia; Brisset, S.; Brochet, P.

doi:10.1109/tmag.2010.2043343

Cited by 15 publications

(12 citation statements)

References 5 publications

(6 reference statements)

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“…MDF þ FP within OSM Results obtained from this process are satisfactory but it is time consuming because the three FE sub-models of the transformer are evaluated several times within OSM algorithm until the convergence of the FP method (Tran et al, 2010).…”

Section: Mdo Formulations Benefitsmentioning

confidence: 99%

Multidisciplinary optimization formulations benefits on space mapping techniques

Ayed

Brisset

2012

COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

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Purpose -The purpose of this paper is to investigate the use of multidisciplinary optimization (MDO) formulations within space-mapping techniques in order to reduce their computing time. Design/methodology/approach -The aim of this work is to quantify the interest of using MDO formulations within space mapping techniques. A comparison of three MDO formulations is carried out in a short time by using an analytical model of a safety transformer. This comparison reveals the advantage of two formulations in terms of robustness and computing time among the three MDO formulations. Then, the best formulations are investigated within output space mapping, using both analytical and FE models of the transformer. Findings -A major computing time gain equal to 5.5 is achieved using the Individual Disciplinary Feasibility formulation within the output space-mapping technique in the case of the safety transformer. Originality/value -The MultiDisciplinary Feasibility formulation is the common formulation used within space-mapping technique because it is the most conventional way to perform MDO. The originality of this paper is to investigate the Individual Disciplinary Feasibility formulation within output space-mapping technique in order to allow the parallelization of calculation and to achieve a major reduction of computing time.

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Section: Mdo Formulations Benefitsmentioning

confidence: 99%

Multidisciplinary optimization formulations benefits on space mapping techniques

Ayed

Brisset

2012

COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

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“…K RIGING, as a type of regression model, is able to predict response surface of the objective function through exploiting the spatial correlation of data which based only on limited information [1]- [3]. However, it was found that large-scale tasks-multi-objective and employing many design variables-may lead to a "combinatorial explosion" when all the required correlation matrices are established between the sample points and the design vectors.…”

Section: Introductionmentioning

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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“…It allows benefiting both from the rapidity of the analytical model (coarse model) and the accuracy of the FEM (fine model) by aligning them (Bandler et al, 1994;Jonathan et al, 2014). The SM technique has been applied successfully for the optimal design of electromagnetic devices, such as linear actuator (Stéphane et al, 2011), transformer (Berbecea et al, 2012Tran et al, 2010) and permanent magnet machine (Legranger et al, 2010). Classically, two models with different granularities are used in the SM technique, the fine model is often FEM, and the coarse model can be an analytical one or a surrogate model, or it can also be a FEM but with coarse mesh.…”

Section: Introductionmentioning

confidence: 99%

“…These different strategies have been compared by Vivier and Friedrich (2016). Several variants of SM have recently been developed, and among these, the most common are the output space mapping (OSM) (Tran et al, 2010) and manifold mapping (MM) (Echeverria et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Comparison of three space mapping techniques on electromagnetic design optimization

Gong

Gillon

Bracikowski

2018

COMPEL

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PurposeThis paper aims to investigate three low-evaluation-budget optimization techniques: output space mapping (OSM), manifold mapping (MM) and Kriging-OSM. Kriging-OSM is an original approach having high-order mapping. Design/methodology/approachThe electromagnetic device to be optimally sized is a five-phase linear induction motor, represented through two levels of modeling: coarse (Kriging model) and fine.The optimization comparison of the three techniques on the five-phase linear induction motor is discussed. FindingsThe optimization results show that the OSM takes more time and iteration to converge the optimal solution compared to MM and Kriging-OSM. This is mainly because of the poor quality of the initial Kriging model. In the case of a high-quality coarse model, the OSM technique would show its domination over the other two techniques. In the case of poor quality of coarse model, MM and Kriging-OSM techniques are more efficient to converge to the accurate optimum. Originality/valueKriging-OSM is an original approach having high-order mapping. An advantage of this new technique consists in its capability of providing a sufficiently accurate model for each objective and constraint function and makes the coarse model converge toward the fine model more effectively.

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Adapted Output Space-Mapping Technique for a Bi-Objective Optimization

Cited by 15 publications

References 5 publications

Multidisciplinary optimization formulations benefits on space mapping techniques

Multidisciplinary optimization formulations benefits on space mapping techniques

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

Comparison of three space mapping techniques on electromagnetic design optimization

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