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Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
TLDR
We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems that always deliver solutions of expected value at least. Expand
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A general approximation technique for constrained forest problems
TLDR
We present a general approximation technique for a large class of graph problems, including the shortest path, minimum spanning tree, minimum-weight perfect matching, traveling salesman and Steiner tree problems. Expand
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The Design of Approximation Algorithms
TLDR
Discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design; to computer science problems in databases; to advertising issues in viral marketing . Expand
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.879-approximation algorithms for MAX CUT and MAX 2SAT
TLDR
We present randomized approximation algorithms for the MAX CUT and MAX 2SAT problems that always deliver solutions of expected value at least .87856 times the optimal value. Expand
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New 3/4-Approximation Algorithms for the Maximum Satisfiability Problem
TLDR
Yannakakis recently presented the first $\frac{3}{4}$-approximation algorithm for the Maximum Satisfiability Problem (MAX SAT). Expand
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The primal-dual method for approximation algorithms and its application to network design problems
TLDR
In the last four decades, combinatorial optimization has been strongly influenced by linear programming. Expand
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Adversarial queueing theory
TLDR
We introduce a new approach to the study of dynamic (or continuous) packet routing, where packets are being continuously injected into a network. Expand
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Adversarial queuing theory
TLDR
We develop an adversarial theory of queuing aimed at addressing some of the restrictions inherent in probabilistic analysis and queuing theory based on time-invariant stochastic generation. Expand
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The Approximability of Constraint Satisfaction Problems
TLDR
We study optimization problems that may be expressed as "Boolean constraint satisfaction problems." An instance of a Boolean constraint satisfaction problem is given by m constraints applied to n Boolean variables. Expand
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Iterative rounding 2-approximation algorithms for minimum-cost vertex connectivity problems
TLDR
The survivable network design problem (SNDP) is the following problem: given an undirected graph and values rij for each pair of vertices i and j, find a minimum-cost subgraph such that there are at least rij disjoint paths between verticesi and j. Expand
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