GCMMA-MMA-Python
This repository contains the Python code of the Method of Moving Asymptotes (Svanberg, 1987), originally developed and written in MATLAB by Krister Svanberg. The original MATLAB code was taken from http://www.smoptit.se/ under the GNU General Public License.
If you opt to use this code, Krister Svanberg would appreciate it if you could send him an email sharing your application and intentions (the email address can be found on his website). When work is published, the authors must cite Krister Svanberg's academic work. The references can be found below.
An example application of the code in topology optimization can be found here.
Installation and usage
The mmapy package is available on PyPi. To install it, use the following command:
pip install mmapy
After installation, you can import the package in your Python script with:
import mmapy
Cite
This repository is linked to Zenodo. To ensure accurate citation of this project and facilitate traceability in case of bugs or issues, please refer to the specific version used, including the DOI from Zenodo. You can find the corresponding DOI on the Zenodo page. Additionally, cite the original work by Krister Svanberg. The relevant references are provided below.
References
- Svanberg, K. (1987). The Method of Moving Asymptotes – A new method for structural optimization. International Journal for Numerical Methods in Engineering 24, 359-373. doi:10.1002/nme.1620240207
- Svanberg, K. (n.d.). MMA and GCMMA – two methods for nonlinear optimization. Retrieved August 3, 2017 from
https://people.kth.se/~krille/mmagcmma.pdf
License
Original work written in MATLAB: Copyright (c) 2006-2009 Krister Svanberg
Derived Python implementation: Copyright (c) 2020-2024 Arjen Deetman
GCMMA-MMA-Python is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License (file LICENSE) along with this file. If not, see http://www.gnu.org/licenses/.
Metadata
Release files for mmapy 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mmapy-0.3.1.tar.gz | 23.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mmapy-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 45.9 kB
Release files / mmapy-0.3.1.tar.gz
| Download URL | mmapy-0.3.1.tar.gz |
|---|---|
| Size | 23.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
185a7c395d6dff741e1283dca07ed417bd0cfc59975fd02ba22d8a14d3c5306a
|
|
BLAKE2b-256 checksum How to use checksums |
9e0d6092211453cfffa302e271b774f5d69a182c9ccd38b75a6c9ba9b23e9fcb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.9.22
|
Release files / mmapy-0.3.1-py3-none-any.whl
| Download URL | mmapy-0.3.1-py3-none-any.whl |
|---|---|
| Size | 22.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
44703a59e06d8c5fbc64913812f1e2df22b43dd1a5a2fe29588c625c17d49d46
|
|
BLAKE2b-256 checksum How to use checksums |
eba7949b8fad0a1e76002748ed2b50dfd87f5d6f0f97a204f957df534c3dd954
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.9.22
|