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Approximation Algorithms for NP-Hard Problems by Dorit Hochbaum

Approximation Algorithms for NP-Hard Problems Dorit Hochbaum ebook
Page: 620
Format: djvu
ISBN: 0534949681, 9780534949686
Publisher: Course Technology

For these problems, approximation algorithms are good choices. Year of my PhD studies at the U of Alberta where I study the theory behind efficient algorithms for combinatorial optimization problems. Most of the problems I study are NP-hard so I focus mainly on approximation algorithms. Maximization and minimization problems) also cannot be solved in polynomial time (unless again P=NP). Hence, the corresponding optimization problems (i.e. As we know, NP-hard problems are nightmare for the computers. In 2003 proved that it is still NP-hard and gave a polynomial-time algorithm with an approximation factor of 1nm. Think about all the effort that's gone into finding approximation algorithms and hardness of approximation results for NP-complete problems. The study of approximation algorithms for NP-hard problems has blossomed into a rich field, especially as a result of intense work over the last two decades. For graph estimation, we consider the problem of estimating forests with restricted tree sizes. Garey and Johnson, in 1978, list various possible ways to "cope" with NP-completeness, including looking for approximate algorithms and for algorithms that are efficient on average. Here is an example to give a feeling.