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

TL;DR

Optipoly is a Python package that efficiently solves box-constrained multivariate polynomial optimization problems, outperforming general NLP solvers in solution quality and computation time.

Contribution

The paper introduces optipoly, a novel Python package specifically designed for polynomial optimization with box constraints, demonstrating superior performance over existing general-purpose solvers.

Findings

Optipoly provides statistically better solutions than NLP solvers.

It achieves significantly reduced computation times.

The package is easy to install and use via pip.

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.