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

Many of the striking advances in theoretical computer science over the past two decades concern approximation algorithms, which compute provably near-optimal solutions to NP-hard optimization problems. It is known that the decisional subset-sum is NP-complete (I believe this result is essentially due to Karp). Algorithms vis-à-vis Everyday Programming; Polynomial-Time Algorithms; NP-Complete Problems. Hence, the corresponding optimization problems (i.e. As we know, NP-hard problems are nightmare for the computers. Perhaps, the best source on approximation algorithms. For these problems, approximation algorithms are good choices. Here is an example to give a feeling. Maximization and minimization problems) also cannot be solved in polynomial time (unless again P=NP). The Travelling-Salesman; Subset-Sum; Set-Covering. Approximation Algorithm for NP-hard problems by Dorit Hochbaum is a set of chapters by different contributors. Approaches include approximation algorithms, heuristics, average-case analysis, and exact exponential-time algorithms: all are essential.