Conflict Optimization for Binary CSP Applied to Minimum Partition into Plane Subgraphs and Graph Coloring
Abstract
CG:SHOP is an annual geometric optimization challenge and the 2022 edition proposed the problem of coloring a certain geometric graph defined by line segments. Surprisingly, the top three teams used the same technique, called conflict optimization. This technique has been introduced in the 2021 edition of the challenge, to solve a coordinated motion planning problem. In this paper, we present the technique in the more general framework of binary constraint satisfaction problems (binary CSP). Then, the top three teams describe their different implementations of the same underlying strategy. We evaluate the performance of those implementations to vertex color not only geometric graphs, but also other types of graphs.
Keywords
Cite
@article{arxiv.2303.09632,
title = {Conflict Optimization for Binary CSP Applied to Minimum Partition into Plane Subgraphs and Graph Coloring},
author = {Loïc Crombez and Guilherme D. da Fonseca and Florian Fontan and Yan Gerard and Aldo Gonzalez-Lorenzo and Pascal Lafourcade and Luc Libralesso and Benjamin Momège and Jack Spalding-Jamieson and Brandon Zhang and Da Wei Zheng},
journal= {arXiv preprint arXiv:2303.09632},
year = {2023}
}
Comments
To appear at ACM Journal of Experimental Algorithmics