Niching genetic algorithms for optimization in electromagnetics. II. Shape optimization of electrodes using the CSM

Sareni, Bruno; Krähenbühl, Laurent; Müller, Dieter

doi:10.1109/20.717698

Cited by 32 publications

(3 citation statements)

References 12 publications

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“… Detailed design models consist in designing the whole component: choosing the geometrical dimensions, the type of material, etc. The complexity depends on the study context : from a simple routine made of analytical equations to a model made of numerical simulations coupled with optimization algorithms [24].  Meta models and response surface approximations (also called surrogate models) is a mathematical method enabling to model analytically a phenomena or a system according to a limited number of references.…”

Section: Evaluation Function : Multi-physical Sizing Processmentioning

confidence: 99%

Optimal design of the Integrated Modular Power Electronics Cabinet

Giraud

Budinger

Roboam

et al. 2016

Aerospace Science and Technology

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This paper deals with a new concept of electrical power distribution system called IMPEC for Integrated Modular Power Electronics Cabinet. The paper defines methods aiming at carrying out an optimal design of IMPEC, the main variables being on one hand the number and size of power electronics module. On the other hand, reconfigurations between these modules and electrical loads are also optimized.The formalization of the problem highlights that designers must deal simultaneously with a combinatorial explosion and a multi-physical system sizing. The main objective of the study is to propose a methodological framework for solving this original optimal design problem. A heuristic-based algorithm is developed to solve this combinatorial optimization problem. A particular attention is paid to develop a weight estimation procedure using generic sizing models. Finally a mapping is performed to identify the best solutions and to highlight the technological components having the most significant sensitivity on the complete system weight.

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Section: Evaluation Function : Multi-physical Sizing Processmentioning

confidence: 99%

Optimal design of the Integrated Modular Power Electronics Cabinet

Giraud

Budinger

Roboam

et al. 2016

Aerospace Science and Technology

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“…The optimal electrode profile from the point B to the point C is given as follows: (8) The problem is solved using the electrode shape optimization method described in [8]. A geometric template has been designed to find an equivalent equipotential to the electrode shape [see Fig.…”

Section: A Principlementioning

confidence: 99%

Efficient genetic algorithms for solving hard constrained optimization problems

2000

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This paper studies many Genetic Algorithm strategies to solve hard-constrained optimization problems. It investigates the role of various genetic operators to avoid premature convergence. In particular, an analysis of niching methods is carried out on a simple function to show advantages and drawbacks of each of them. Comparisons are also performed on an original benchmark based on an electrode shape optimization technique coupled with a charge simulation method.Index Terms-Constrained optimization methods, genetic algorithms, niching methods, shape optimization methods.

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“…The question then is how can several minima in a particular design space be identified simultaneously? One proposed solution (Sareni et al, 1997a;1997b) is to use a genetic algorithm which explores the design space with several populations, or`n iches'' rather than just one. The niches are designed to span the design space and individuals are assigned to niches using a Hamming distance calculation based on a binary string which encodes the parameters of the device.…”

Section: Introductionmentioning

confidence: 99%