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Computer Science > Computational Engineering, Finance, and Science

arXiv:2411.05689 (cs)
[Submitted on 8 Nov 2024]

Title:optipoly: A Python package for boxed-constrained multi-variable polynomial cost functions optimization

Authors:Mazen Alamir
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Abstract:In this paper, a new python package (optipoly) is described that solves box-constrained optimization problem over multivariate polynomial cost functions. The principle of the algorithm is described before its performance is compared to three general purpose NLP solvers implemented in the state-of-the-art Gekko and scipy packages. The comparison show statistically better best solution provided by the algorithm with significantly less computation times. The package will be shortly made freely and easily available through the simple (pip install) process.
Comments: 18 pages, 6 figures, 3 tables
Subjects: Computational Engineering, Finance, and Science (cs.CE)
Cite as: arXiv:2411.05689 [cs.CE]
  (or arXiv:2411.05689v1 [cs.CE] for this version)
  https://doi.org/10.48550/arXiv.2411.05689

Submission history

From: Mazen Alamir Prof [view email]
[v1] Fri, 8 Nov 2024 16:39:26 UTC (1,502 KB)
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