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Results 1 - 10
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9,518
The approximability of NP-hard problems
- In Proceedings of the Annual ACM Symposium on Theory of Computing
, 1998
"... Many problems in combinatorial optimization are NP-hard (see [60]). This has forced researchers to explore techniques for dealing with NP-completeness. Some have considered algorithms that solve “typical” ..."
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Cited by 17 (0 self)
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Many problems in combinatorial optimization are NP-hard (see [60]). This has forced researchers to explore techniques for dealing with NP-completeness. Some have considered algorithms that solve “typical”
Local Search for NP-Hard Problems
, 1997
"... To date, computer scientists believe that NP-Hard problems cannot be solved by algorithms which run in less than exponential time in the worst case. One way to approach these problems is to design algorithms that do not guarantee a solution to every problem instance, but which solve many if not mo ..."
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Cited by 3 (0 self)
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To date, computer scientists believe that NP-Hard problems cannot be solved by algorithms which run in less than exponential time in the worst case. One way to approach these problems is to design algorithms that do not guarantee a solution to every problem instance, but which solve many
The Approximability of Some NP-hard Problems
, 2009
"... An α-approximation algorithm is an algorithm guaranteed to output a solution that is within an α ratio of the optimal solution. We are interested in the following question: Given an NP-hard optimization problem, what is the best approximation guarantee that any polynomial time algorithm could achiev ..."
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An α-approximation algorithm is an algorithm guaranteed to output a solution that is within an α ratio of the optimal solution. We are interested in the following question: Given an NP-hard optimization problem, what is the best approximation guarantee that any polynomial time algorithm could
Exact Algorithms for NP-Hard Problems
- Lecture Notes in Computer Science, SpringerVerlag Heidelberg, Volume 2570
, 2003
"... A survey ..."
The Fault Tolerance of NP-Hard Problems
"... Abstract. We study the effects of faulty data on NP-hard sets. We consider hard sets for several polynomial time reductions, add corrupt data and then analyze whether the resulting sets are still hard for NP. We explain that our results are related to a weakened deterministic variant of the notion o ..."
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Abstract. We study the effects of faulty data on NP-hard sets. We consider hard sets for several polynomial time reductions, add corrupt data and then analyze whether the resulting sets are still hard for NP. We explain that our results are related to a weakened deterministic variant of the notion
Approximation Algorithms for NP-Hard Problems
- MATHEMATISCHES FORSCHUNGSINSTITUT OBERWOLFACH REPORT NO. 28/2004
, 2004
"... ..."
Approximation Algorithms for NP-Hard Problems
- MATHEMATISCHES FORSCHUNGSINSTITUT OBERWOLFACH REPORT NO. 28/2004
, 2004
"... ..."
Rigorous analysis of heuristics for NP-hard problems
- In Proceedings of the 16 th annual ACM-SIAM Symposium on Discrete Algorithms
, 2005
"... The known NP-hardness results imply that for many combinatorial optimization problems there are no efficient algorithms that find an optimal solution, or even a near optimal solution, on every instance. A heuristic for an NP-hard problem is a polynomial time algorithm that produces optimal or near o ..."
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Cited by 2 (0 self)
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The known NP-hardness results imply that for many combinatorial optimization problems there are no efficient algorithms that find an optimal solution, or even a near optimal solution, on every instance. A heuristic for an NP-hard problem is a polynomial time algorithm that produces optimal or near
Test Instance Construction for NP-hard Problems
, 1987
"... The performance of heuristic approximation algorithms for NP-hard problems can often only be determined by experimentation. This paper explores some of the issues involved in the efficient generation of useful test sets for such problems, i.e. test sets consisting of instances of the problem for whi ..."
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Cited by 1 (1 self)
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The performance of heuristic approximation algorithms for NP-hard problems can often only be determined by experimentation. This paper explores some of the issues involved in the efficient generation of useful test sets for such problems, i.e. test sets consisting of instances of the problem
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