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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.13420 |
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| _version_ | 1866910575720660992 |
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| author | Joshy, Anugrah Jo Hwang, John T. |
| author_facet | Joshy, Anugrah Jo Hwang, John T. |
| contents | PySLSQP is a seamless interface for using the SLSQP algorithm from Python. It wraps the original SLSQP Fortran code sourced from the SciPy repository and provides a host of new features to improve the research utility of the original algorithm. Some of the additional features offered by PySLSQP include auto-generation of unavailable derivatives using finite differences, independent scaling of the problem variables and functions, access to internal optimization data, live-visualization, saving optimization data from each iteration, warm/hot restarting of optimization, and various other utilities for post-processing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_13420 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | PySLSQP: A transparent Python package for the SLSQP optimization algorithm modernized with utilities for visualization and post-processing Joshy, Anugrah Jo Hwang, John T. Mathematical Software Numerical Analysis G.1.6; J.2 PySLSQP is a seamless interface for using the SLSQP algorithm from Python. It wraps the original SLSQP Fortran code sourced from the SciPy repository and provides a host of new features to improve the research utility of the original algorithm. Some of the additional features offered by PySLSQP include auto-generation of unavailable derivatives using finite differences, independent scaling of the problem variables and functions, access to internal optimization data, live-visualization, saving optimization data from each iteration, warm/hot restarting of optimization, and various other utilities for post-processing. |
| title | PySLSQP: A transparent Python package for the SLSQP optimization algorithm modernized with utilities for visualization and post-processing |
| topic | Mathematical Software Numerical Analysis G.1.6; J.2 |
| url | https://arxiv.org/abs/2408.13420 |