Abstract
IN THE first chapter we have seen that, due to their inherent complexity, Np-hard optimization problems cannot be efficiently solved in an exact way, unless P = Np. Therefore, if we want to solve an Np-hard optimization problem by means of an efficient (polynomial-time) algorithm, we have to accept the fact that the algorithm does not always return an optimal solution but rather an approximate one. In Chap. 2, we have seen that, in some cases, standard algorithm design techniques, such as local search or greedy techniques, although inadequate to obtain the optimal solution of Np-hard optimization problems, are powerful enough to reach good approximate solutions in polynomial time.
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© 1999 Springer-Verlag Berlin Heidelberg
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Ausiello, G., Marchetti-Spaccamela, A., Crescenzi, P., Gambosi, G., Protasi, M., Kann, V. (1999). Approximation Classes. In: Complexity and Approximation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-58412-1_3
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DOI: https://doi.org/10.1007/978-3-642-58412-1_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-63581-6
Online ISBN: 978-3-642-58412-1
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