A Python library for developing customized optimization algorithms under general paradigms like simulated annealing and branch and bound. Also features continuous training, so algorithms can be run multiple times and resume from where they left off in previous runs.
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2 maintainers
Release files for optimizn 0.0.24
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| optimizn-0.0.24.tar.gz | 42.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| optimizn-0.0.24-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 102.5 kB
Release files / optimizn-0.0.24.tar.gz
| Download URL | optimizn-0.0.24.tar.gz |
|---|---|
| Size | 42.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.9
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Release files / optimizn-0.0.24-py3-none-any.whl
| Download URL | optimizn-0.0.24-py3-none-any.whl |
|---|---|
| Size | 60.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.9
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