An Approximation Algorithm for Covering Linear Programs and its Application to Bin-Packing

Abstract

We give an $\alpha (1+\epsilon )$-approximation algorithm for solving covering LPs, assuming the presence of a $(1/\alpha )$-approximation algorithm for a certain optimization problem. Our algorithm is based on a simple modification of the Plotkin-Shmoys-Tardos algorithm (MOR 1995). We then apply our algorithm to $\alpha (1+\epsilon )$-approximately solve the configuration LP for a large class of bin-packing problems, assuming the presence of a $(1/\alpha )$-approximate algorithm for the corresponding knapsack problem (KS). Previous results give us a PTAS for the configuration LP using a PTAS for KS. Those results don't extend to the case where KS is poorly approximated. Our algorithm, however, works even for polynomially-large $\alpha$.

Update: added acknowledgements