Complexity of Coloring Random Graphs

Author:

Mann Zoltán Ádám1ORCID

Affiliation:

1. University of Duisburg-Essen, Germany

Abstract

It is known that the problem of deciding k -colorability of a graph exhibits an easy-hard-easy pattern,—that is, the average-case complexity for backtrack-type algorithms, as a function of k , has a peak. This complexity peak is either at k = χ − 1 or k = χ, where χ is the chromatic number of the graph. However, the behavior around the complexity peak is poorly understood. In this article, we use list coloring to model coloring with a fractional number of colors between χ − 1 and χ. We present a comprehensive computational study on the complexity of backtrack-type graph coloring algorithms in this critical range. According to our findings, an easy-hard-easy pattern can be observed on a finer scale between χ − 1 and χ as well. The highest complexity found this way can be higher than for any integer value of k . It turns out that the complexity follows an alternating three-dimensional pattern; understanding this pattern is very important for benchmarking purposes. Our results also answer the previously open question whether coloring with χ − 1 or with χ colors is harder: this depends on the location of the maximal fractional complexity.

Funder

János Bolyai Research Scholarship of the Hungarian Academy of Sciences

Hungarian Scientific Research Fund

Publisher

Association for Computing Machinery (ACM)

Subject

Theoretical Computer Science

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. RECYCLING SOLUTIONS FOR VERTEX COLORING HEURISTICS;Journal of the Operations Research Society of Japan;2021-07-31

2. Comparative Analysis of the main Graph Coloring Algorithms;2021 IEEE Colombian Conference on Communications and Computing (COLCOM);2021-05-26

3. Complexity Analysis and Stochastic Convergence of Some Well-known Evolutionary Operators for Solving Graph Coloring Problem;Mathematics;2020-02-25

4. Understanding the Empirical Hardness of Random Optimisation Problems;Lecture Notes in Computer Science;2019

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