English

An error analysis for polynomial optimization over the simplex based on the multivariate hypergeometric distribution

Optimization and Control 2014-07-09 v1

Abstract

We study the minimization of fixed-degree polynomials over the simplex. This problem is well-known to be NP-hard, as it contains the maximum stable set problem in graph theory as a special case. In this paper, we consider a rational approximation by taking the minimum over the regular grid, which consists of rational points with denominator rr (for given rr). We show that the associated convergence rate is O(1/r2)O(1/r^2) for quadratic polynomials. For general polynomials, if there exists a rational global minimizer over the simplex, we show that the convergence rate is also of the order O(1/r2)O(1/r^2). Our results answer a question posed by De Klerk et al. (2013) and improves on previously known O(1/r)O(1/r) bounds in the quadratic case.

Keywords

Cite

@article{arxiv.1407.2108,
  title  = {An error analysis for polynomial optimization over the simplex based on the multivariate hypergeometric distribution},
  author = {Etienne de Klerk and Monique Laurent and Zhao Sun},
  journal= {arXiv preprint arXiv:1407.2108},
  year   = {2014}
}

Comments

17 pages

R2 v1 2026-06-22T04:58:18.062Z