The near exact bin covering problem

TL;DR

This paper introduces a new generalization of the bin covering problem called the near exact bin covering problem, which is strongly NP-hard, and provides an AFPTAS for the case when the allowed deviation is a constant.

Contribution

The paper presents the first asymptotic fully polynomial time approximation scheme for the near exact bin covering problem with a constant deviation.

Findings

No bounded approximation exists for variable Δ unless P=NP.

An AFPTAS is developed for constant Δ.

The problem generalizes the classical bin covering problem.

Abstract

We present a new generalization of the bin covering problem that is known to be a strongly NP-hard problem. In our generalization there is a positive constant $\Delta$, and we are given a set of items each of which has a positive size. We would like to find a partition of the items into bins. We say that a bin is near exact covered if the total size of items packed into the bin is between $1$ and $1+\Delta$. Our goal is to maximize the number of near exact covered bins. If $\Delta=0$ or $\Delta>0$ is given as part of the input, our problem is shown here to have no approximation algorithm with a bounded asymptotic approximation ratio (assuming that $P\neq NP$). However, for the case where $\Delta>0$ is seen as a constant, we present an asymptotic fully polynomial time approximation scheme (AFPTAS) that is our main contribution.