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borealis

Optimization script for discretized equation

https://github.com/ytakahashi3123/borealis

Science Score: 57.0%

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Repository

Optimization script for discretized equation

Basic Info
  • Host: GitHub
  • Owner: ytakahashi3123
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 38.2 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 4
Created about 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License Citation

README.md

Borealis

Bayesian optimization for finding realizable solutions for discretized equation

Code description

Borealis solves an inverse problem in various mathematical models based on the Bayesian optimization and swarm intelligence algorithm. This software is designed to evaluate an objective function based on the user's program output data and to optimize by changing input parameters. User programs serve as adapters, allowing Borealis to execute and optimize via the user's input configuration file. Templates for adapter programs are provided. The Bayesian optimization, the particle swarm optimization (PSO) algorithm, the artificial bee colony (ABC) algorithm, and the genetic algorithm (GA) are implemented as optimizers. PSO also supports distributed parallel processing using mpi4py. The following animation is an example of optimization for estimating input heat flux in heat conduction analysis.

Optimization process for estimating input heat flux in heat conduction analysis.\label{fig:optimization}

How to start optimization

Install Borealis

Download ZIP of this repository

or

console git clone https://github.com/ytakahashi3123/borealis.git

Run Borealis

console python3 src/borealis.py

Tutorial case: testcase/work* The tutorials recommended are testcase/work_example_externalcode and testcase/work_simple_function

Configuration file

Optimization by Borealis is controled by the configuration file: borealis.yml.

External code

When an external code, for example, Tacode, is used, the pass needs to be specified in borealis.yml and file permissions also be given.

Requirements

Borealis requires the following packages:

  • numpy (>=1.22.3)
  • yaml (>= 5.3.1)
  • GPyOpt (>= 1.2.6)
  • mpi4py (>=3.0.3)

Contact:

Yusuke Takahashi, Hokkaido University

ytakahashi@eng.hokudai.ac.jp

References

  • Yusuke Takahashi, Masahiro Saito, Nobuyuki Oshima, and Kazuhiko Yamada, “Trajectory Reconstruction for Nanosatellite in Very Low Earth Orbit Using Machine Learning.” Acta Astronautica 194: 301–8. 2022. https://doi.org/https://doi.org/10.1016/j.actaastro.2022.02.010.

Owner

  • Name: Yusuke Takahashi
  • Login: ytakahashi3123
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.3.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Takahashi
  given-names: Yusuke
orcid: https://orcid.org/0000-0002-6272-5758
title: "Borealis: Bayesian optimization for finding realizable solutions for discretized equation"
version: v1.3.0
date-released: 2024-07-21
url: "https://github.com/ytakahashi3123/borealis"

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