Exploiting Algebraic Structure in Global Optimization and the Belgian Chocolate Problem

TL;DR

This paper introduces a novel algebraic approach for globally optimizing the Belgian chocolate problem, efficiently finding the maximum parameter value by exploiting polynomial structure, surpassing previous iterative methods.

Contribution

The paper presents a non-iterative algebraic method that directly computes large limiting values of the parameter, improving over prior iterative optimization techniques.

Findings

Largest known value of δ: 0.9808348

Method recovers known bounds in low degree cases

Prior methods converge towards the new δ value

Abstract

The Belgian chocolate problem involves maximizing a parameter {\delta} over a non-convex region of polynomials. In this paper we detail a global optimization method for this problem that outperforms previous such methods by exploiting underlying algebraic structure. Previous work has focused on iterative methods that, due to the complicated non-convex feasible region, may require many iterations or result in non-optimal {\delta}. By contrast, our method locates the largest known value of {\delta} in a non-iterative manner. We do this by using the algebraic structure to go directly to large limiting values, reducing the problem to a simpler combinatorial optimization problem. While these limiting values are not necessarily feasible, we give an explicit algorithm for arbitrarily approximating them by feasible {\delta}. Using this approach, we find the largest known value of {\delta} to date, {\delta} = 0.9808348. We also demonstrate that in low degree settings, our method recovers previously known upper bounds on {\delta} and that prior methods converge towards the {\delta} we find.