Optimization algorithms for the centroidal Voronoi tessellation of particles

• OGINO Masao

  Daido University

Bibliographic Information

Other Title

• 粒子の重心ボロノイ分割配置に対する最適化アルゴリズム

Abstract

This paper describes optimization algorithms as numerical methods to find the centroidal Voronoi tessellation (CVT). The CVT can expect to put particles at evenly spaced apart with capturing the curvature of the boundary and then generate an efficient initial particle distribution for the particle methods to analyze the fluid flow problems with slopes and curved walls. However, a problem to find CVT is classified as the NP-hard. Therefore, there is a great demand for an algorithm to solve the problem efficiently. This paper considers finding CVT as optimization problem about finding minimum energy and then applies optimizers in the field of machine learning such as the Momentum SGD and the Adam. Moreover, this paper discusses on hyperparameters of optimizers and performances of iteration counts to find CVT.

Journal

• Transactions of the Japan Society for Computational Engineering and Science

  Transactions of the Japan Society for Computational Engineering and Science 2020 (1), 20201002-20201002, 2020-10-28

  JAPAN SOCIETY FOR COMPUTATIONAL ENGINEERING AND SCIENCE

Keywords

• Centroidal Voronoi Tessellation
• Initial Particle Distribution
• Optimizers
• Machine Learning
• Particle Method

Details

• CRID: 1391412326421296256
• NII Article ID: 130007930927
• DOI: 10.11421/jsces.2020.20201002
• ISSN: 13478826
• Text Lang: ja
• Data Source:
  • JaLC
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed