Fast Multi-objective Optimization of Magnetic Shield Shape by Combining Auto-Encoder and Level-set Method

Kanae Oda, Ryota Kawamata, Shinji Wakao, Noboru Murata

Research output: Contribution to journalArticlepeer-review

Abstract

We proposed a new multi-objective optimization approach combining both gradient calculation in actual high-dimensional design space and that in a low-dimensional latent space that is an appropriately compressed design space with Auto-Encoder. The proposed approach enables us to quickly and precisely search for more global pareto solution group in multi-objective optimization by using the optimization results in the low-dimensional space as the initial value of the gradient calculation in the actual design space.

Original languageEnglish
JournalIEEE Transactions on Magnetics
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Auto-Encoder
  • Convolution
  • Decoding
  • Estimation
  • Latent variables
  • Level-set method
  • Linear programming
  • Multi-objective optimization
  • Optimization
  • Pareto solutions
  • Shape
  • Training

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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