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Titlebook: Complexity and Approximation; Combinatorial Optimi Giorgio Ausiello,Alberto Marchetti-Spaccamela,Vigg Textbook 1999 Springer-Verlag Berlin

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J. David Alvis,Jason R. Jividen many problems arising in different areas: taking into account the scope of this book, however, we will limit ourselves to considering randomized approximation algorithms for N.-hard optimization problems.
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J. David Alvis,Jason R. Jividenecise machine-based characterization that will be used in Sect. 6.3 to develop the notion of . (in short, PCP). In Sect. 6.4 we will see how probabilistically checkable proofs can be used in a rather surprising way to show non-approximability results for N.-hard optimization problems.
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Fostering Statesmanship in Public Life,of a P. result, we first show that any NP problem admits long (that is, exponential) proofs which can be verified with a constant number of queries. To this aim we introduce the arithmetization of a Boolean formula and we make use of some properties of linear functions.
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The Regime for Bank Regulation,IN THE preceding chapter we observed that many relevant optimization problems are N.-hard, and that it is unlikely that we will ever be able to find efficient (i.e., polynomial-time) algorithms for their solution. In such cases it is worth looking for algorithms that always return a feasible solution whose measure is not too far from the optimum.
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