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Pipage Rounding: A New Method of Constructing Algorithms with Proven Performance Guarantee
TLDR
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
A note on maximizing a submodular set function subject to a knapsack constraint
TLDR
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
The Santa Claus problem
TLDR
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
Approximation schemes for minimizing average weighted completion time with release dates
TLDR
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
An Improved Approximation Algorithm for the Metric Uncapacitated Facility Location Problem
TLDR
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
Non-monotone submodular maximization under matroid and knapsack constraints
TLDR
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
Approximation algorithms for asymmetric TSP by decomposing directed regular multigraphs
TLDR
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
Improved approximation algorithms for multidimensional bin packing problems
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
Approximation Algorithms for Maximum Coverage and Max Cut with Given Sizes of Parts
TLDR
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
Buffer Overflow Management in QoS Switches
TLDR
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
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