English

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

Computational Engineering, Finance, and Science 2025-03-27 v2

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.

Keywords

Cite

@article{arxiv.2411.05689,
  title  = {optipoly: A Python package for boxed-constrained multi-variable polynomial cost functions optimization},
  author = {Mazen Alamir},
  journal= {arXiv preprint arXiv:2411.05689},
  year   = {2025}
}

Comments

18 pages, 6 figures, 3 tables