Approximation Algorithms and LP Relaxations for Scheduling Problems Related to Min-Sum Set Cover
Abstract
We consider single-machine scheduling problems that are natural generalizations or variations of the min-sum set cover problem and the min-sum vertex cover problem. For each of these problems, we give new approximation algorithms. Some of these algorithms rely on time-indexed LP relaxations. We show how a variant of alpha-point scheduling leads to the best-known approximation ratios, including a guarantee of 4 for an interesting special case of the so-called generalized min-sum set cover problem. We also make explicit the connection between the greedy algorithm for min-sum set cover and the concept of Sidney decomposition for precedence-constrained single-machine scheduling, and show how this leads to a 4-approximation algorithm for single-machine scheduling with so-called bipartite OR-precedence constraints.
Cite
@article{arxiv.2001.07011,
title = {Approximation Algorithms and LP Relaxations for Scheduling Problems Related to Min-Sum Set Cover},
author = {Felix Happach and Andreas S. Schulz},
journal= {arXiv preprint arXiv:2001.07011},
year = {2020}
}