A Comparison of Random Task Graph Generation Methods for Scheduling Problems
Abstract
How to generate instances with relevant properties and without bias remains an open problem of critical importance for a fair comparison of heuristics. In the context of scheduling with precedence constraints, the instance consists of a task graph that determines a partial order on task executions. To avoid selecting instances among a set populated mainly with trivial ones, we rely on properties that quantify the characteristics specific to difficult instances. Among numerous identified such properties, the mass measures how much a task graph can be decomposed into smaller ones. This property, together with an in-depth analysis of existing random task graph generation methods, establishes the sub-exponential generic time complexity of the studied problem. Empirical observations on the impact of existing generation methods on scheduling heuristics concludes our study.
Cite
@article{arxiv.1902.05808,
title = {A Comparison of Random Task Graph Generation Methods for Scheduling Problems},
author = {Louis-Claude Canon and Mohamad El Sayah and Pierre-Cyrille Héam},
journal= {arXiv preprint arXiv:1902.05808},
year = {2019}
}