1997
DOI: 10.1109/20.582631
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Design optimization of a superferric octupole using various evolutionary and deterministic techniques

Abstract: The paper describes different strategies for the design optimization of electromagnets. In order to compare the efficiency of these procedures, the same objective weighting function was minimized using a deterministic search algorithm, evolution strategy, and genetic algorithms. The objective function is based on minimizing the relative normal multipoles produced by the harmonic analysis of the flux density produced by the pole. The pole shape was treated differently in applying the various techniques to the p… Show more

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Cited by 6 publications
(3 citation statements)
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References 8 publications
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“…T HE USE of a genetic algorithm (GA) requires the choice of a set of genetic operations between many possibilities [1]. For example, the crossover operation with two cut points, mutation bit by bit, and selection based on the roulette well.…”
Section: Introductionmentioning
confidence: 99%
“…T HE USE of a genetic algorithm (GA) requires the choice of a set of genetic operations between many possibilities [1]. For example, the crossover operation with two cut points, mutation bit by bit, and selection based on the roulette well.…”
Section: Introductionmentioning
confidence: 99%
“…During the second step (final design) a three dimensional finite element model is used [1] in order to account for both the complicated geometry of the air-gap and iron saturation. This second stage enables a more detailed analysis of the machine and can be used in conjunction with a minimizing procedure in order to optimize the claw geometry in the specific application [2][3][4].…”
Section: Design Proceduresmentioning
confidence: 99%
“…However, the optimization of the rotor geometry may require laborious and expensive numerical schemes especially when 3D configuration should be considered [4,5]. Although both stochastic [6] and deterministic optimization algorithms can be implemented [7][8][9], the sensitivity analysis technique combined with finite element methods enables robust and fast convergence [1].…”
Section: Introductionmentioning
confidence: 99%