Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
More complicated questions about maxima and minima, and some closures of NP
Theoretical Computer Science
The complexity of optimization problems
Journal of Computer and System Sciences - Structure in Complexity Theory Conference, June 2-5, 1986
Efficient solution of linear diophantine equations
Journal of Symbolic Computation
SIAM Journal on Computing
It is hard to know when greedy is good for finding independent sets
Information Processing Letters
A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
Information Processing Letters
On the hardness of approximating minimization problems
Journal of the ACM (JACM)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Theta2p-Completeness: A Classical Approach for New Results
FST TCS 2000 Proceedings of the 20th Conference on Foundations of Software Technology and Theoretical Computer Science
Two remarks on the power of counting
Proceedings of the 6th GI-Conference on Theoretical Computer Science
Approximation algorithms for combinatorial problems
Journal of Computer and System Sciences
The cluster editing problem: implementations and experiments
IWPEC'06 Proceedings of the Second international conference on Parameterized and Exact Computation
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For both the edge deletion heuristic and the maximum-degree greedy heuristic, we study the problem of recognizing those graphs for which that heuristic can approximate the size of a minimum vertex cover within a constant factor of r, where r is a fixed rational number. Our main results are that these problems are complete for the class of problems solvable via parallel access to NP. To achieve these main results, we also show that the restriction of the vertex cover problem to those graphs for which either of these heuristics can find an optimal solution remains NP-hard.