The paper presents a general method of designing constant-factor approximation algorithms for some discrete optimization problems with assignment-type constraints with better performance guarantees for some well-known problems including MAXIMUM COVERAGE, MAX CUT and some of their generalizations.Expand

An (1-e^-^1)-approximation algorithm for maximizing a nondecreasing submodular set function subject to a knapsack constraint is obtained and requires O(n^5) function value computations.Expand

This work considers the following problem: The Santa Claus has n presents that he wants to distribute among m kids, each kid has an arbitrary value for each present, and develops an O(log log m/log log log m) approximation algorithm for the restricted assignment case of the problem when p<sub>ij</sub>,0 (i.e. when present j has either value p <sub>j</sub> or 0 for each kid).Expand

This work presents the first known polynomial time approximation schemes for several variants of the problem of scheduling n jobs with release dates on m machines so as to minimize their average weighted completion time.Expand

A new approximation algorithm for the metric uncapacitated facility location problem is designed, of LP rounding type and is based on a rounding technique developed in [5,6,7].Expand

This paper gives the first constant-factor approximation algorithm for maximizing any non-negative submodular function subject to multiple matroid or knapsack constraints, and improves the approximation guarantee of the algorithm to 1/k+1+{1/k-1}+ε for k≥2 partition matroid constraints.Expand

It is proved that if the d-regular multigraph does not contain more than ⌊d/2⌋ copies of any 2-cycle then it can be found a similar decomposition into n2 pairs of cycle covers where each 2- cycle occurs in at most one component of each pair.Expand

In this paper we introduce a new general framework for set covering problems, based on the combination of randomized rounding of the (near-)optimal solution of the linear programming (LP) relaxation,… Expand

A general method of designing constant-factor approximation algorithms for some discrete optimization problems with cardinality constraints by using a simple deterministic procedure of rounding of linear relaxations to design a (1-(1-1/k)k)-approximation algorithm for the maximum coverage problem.Expand

It is proved that the greedy algorithm that drops the earliest packets among all low-value packets is the best greedy algorithm, and the competitive ratio of any on-line algorithm for a uniform bounded-delay buffer is bounded away from 1, independent of the delay size.Expand