Pritchard, DavidChakrabarty, Deeparnab2010-08-212010-08-212010-08-21201010.1007/s00453-010-9431-zhttps://infoscience.epfl.ch/handle/20.500.14299/52336WOS:0002914819000050904.0859The main focus of this paper is a pair of new approximation algorithms for certain integer programs. First, for covering integer programs {min cx:Ax≥b,0≤x≤d} where A has at most k nonzeroes per row, we give a k-approximation algorithm. (We assume A,b,c,d are nonnegative.) For any k≥2 and ε>0, if P≠NP this ratio cannot be improved to k−1−ε, and under the unique games conjecture this ratio cannot be improved to k−ε. One key idea is to replace individual constraints by others that have better rounding properties but the same nonnegative integral solutions; another critical ingredient is knapsack-cover inequalities. Second, for packing integer programs {max cx:Ax≤b,0≤x≤d} where A has at most k nonzeroes per column, we give a (2k 2+2)-approximation algorithm. Our approach builds on the iterated LP relaxation framework. In addition, we obtain improved approximations for the second problem when k=2, and for both problems when every A ij is small compared to b i . Finally, we demonstrate a 17/16-inapproximability for covering integer programs with at most two nonzeroes per column.Integer programmingApproximation algorithmsLP roundingVertex CoverApproximation Algorithms2 VariablesPackingtext::journal::journal article::research article