AbstractWe define a natural variant of NP, MAX NP, and also a subclass called MAX SNP. These are classes of optimization problems, and in fact contain several natural, well-studied ones. We show that problems in these classes can be approximated with some bounded error. Furthermore, we show that a number of common optimization problems are complete for MAX SNP under a kind of careful transformation (called L-reduction) that preserves approximability. It follows that such a complete problem has a polynomial-time approximation scheme iff the whole class does. These results may help explain the lack of progress on the approximability of a host of optimization problems
An α-approximation algorithm is an algorithm guaranteed to output a solution that is within an α rat...
AbstractFixed-parameter tractability of NP optimization problems is studied by relating it to approx...
In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibili...
AbstractWe define a natural variant of NP, MAX NP, and also a subclass called MAX SNP. These are cla...
We define a natural variant of NP, MAX NP, and also a subclass called MAX SNP. These are classes of ...
AbstractWe investigate the relationship between logical expressibility of NP optimization problems a...
AbstractWe investigate the relationship between logical expressibility of NP optimization problems a...
We investigate the relationship between logical expressibility of NP optimization problems and thei...
AbstractWe introduce a formal framework for studying approximation properties of NP optimization (NP...
AbstractWe introduce a formal framework for studying approximation properties of NP optimization (NP...
AbstractThis paper presents the main results obtained in the field of approximation algorithms in a ...
AbstractIn this paper we study NP optimization problems from the perspective of descriptive complexi...
In this paper we deal with the class NCX of NP Optimization problems that are approximable within co...
In this paper we deal with the class NCX of NP Optimization problems that are approximable within co...
. In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibi...
An α-approximation algorithm is an algorithm guaranteed to output a solution that is within an α rat...
AbstractFixed-parameter tractability of NP optimization problems is studied by relating it to approx...
In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibili...
AbstractWe define a natural variant of NP, MAX NP, and also a subclass called MAX SNP. These are cla...
We define a natural variant of NP, MAX NP, and also a subclass called MAX SNP. These are classes of ...
AbstractWe investigate the relationship between logical expressibility of NP optimization problems a...
AbstractWe investigate the relationship between logical expressibility of NP optimization problems a...
We investigate the relationship between logical expressibility of NP optimization problems and thei...
AbstractWe introduce a formal framework for studying approximation properties of NP optimization (NP...
AbstractWe introduce a formal framework for studying approximation properties of NP optimization (NP...
AbstractThis paper presents the main results obtained in the field of approximation algorithms in a ...
AbstractIn this paper we study NP optimization problems from the perspective of descriptive complexi...
In this paper we deal with the class NCX of NP Optimization problems that are approximable within co...
In this paper we deal with the class NCX of NP Optimization problems that are approximable within co...
. In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibi...
An α-approximation algorithm is an algorithm guaranteed to output a solution that is within an α rat...
AbstractFixed-parameter tractability of NP optimization problems is studied by relating it to approx...
In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibili...