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

€� traveling salesperson problem, Steiner tree. For these problems, approximation algorithms are good choices. Algorithms vis-à-vis Everyday Programming; Polynomial-Time Algorithms; NP-Complete Problems. Many Problems are NP-Complete Does P=NP Coping with NP-Completeness The Vertex Cover Problem Smarter Brute-Force Search. Even if P is not equal to NP, there may be randomized algorithms (either Monte Carlo or Las Vegas) that can answer NP hard problems rapidly. Here is an example to give a feeling. Approximation algorithms for NP-hard problems. The Travelling-Salesman; Subset-Sum; Set-Covering. With Christos Papadimitriou in 1988, he framed the systematic study of approximation algorithms for {\mathsf{NP}} -hard optimization problems around the classes {\mathsf{MaxNP}} and {\mathsf{MaxSNP}} . The problem is NP-hard and an approximation algorithm has been described in the reference. A less obvious application is that the minimum spanning tree can be used to approximately solve the traveling salesman problem. As we know, NP-hard problems are nightmare for the computers. NP-complete problems are often addressed by using approximation algorithms. My answer is that is it ignores randomized and approximation algorithms. Approximation Algorithms for NP-Hard Problems. Numerous practical problems are integer optimization problems that are intractable.