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Approximation Algorithms for NP-Hard Problems
Approximation Algorithms for NP-Hard Problems

Approximation Algorithms for NP-Hard Problems. Dorit Hochbaum

Approximation Algorithms for NP-Hard Problems


Approximation.Algorithms.for.NP.Hard.Problems.pdf
ISBN: 0534949681,9780534949686 | 620 pages | 16 Mb


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Approximation Algorithms for NP-Hard Problems Dorit Hochbaum
Publisher: Course Technology




Perhaps, the best source on approximation algorithms. We present integer programs for both GOPs that provide exact solutions. Most of the problems I study are NP-hard so I focus mainly on approximation algorithms. Year of my PhD studies at the U of Alberta where I study the theory behind efficient algorithms for combinatorial optimization problems. Approximation Algorithms for NP-Hard Problems by Dorit Hochbaum. Hence, the corresponding optimization problems (i.e. Approximation Algorithm for NP-hard problems by Dorit Hochbaum is a set of chapters by different contributors. Maximization and minimization problems) also cannot be solved in polynomial time (unless again P=NP). We show both problems to be NP-hard and prove limits on approximation for both problems. In this problem, multiple missions compete for sensor resources. Approximation Algorithms for NP-Hard Problems pdf download. They showed that this problem is NP-hard even to approximate, and presented several heuristic algorithms. Since many interesting optimization problems are computationally intractable (NP-Hard), we resort to designing approximation algorithms which provably output good solutions. The reason the Cooper result holds is essentially that Bayes nets can be used to encode boolean satisfiability (SAT) problems, so solving the generic Bayes net inference problem lets you solve any SAT problem. Because all of these problems are NP-hard, the primary goal of this research is to produce polynomial-time, approximation algorithms for each problem considered.

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