AbstractWe introduce a formal framework for studying approximation properties of NP optimization (NPO) problems. The classes of approximable problems we consider are those appearing in the literature, namely the class of approximable problems within a constant ε (APX), and the class of problems having a polynomial time approximation scheme (PTAS). We define natural approximation preserving reductions and obtain completeness results in NPO, APX, and PTAS. A complete problem in a class cannot have stronger approximation properties unless P = NP. We also show that the degree structure of NPO allows intermediate degrees, that is, if P ≠ NP, there are problems which are neither complete nor belong to a lower class
We investigate the relationship between logical expressibility of NP optimization problems and thei...
The fact that polynomial time algorithm is very unlikely to be devised for an optimal solving of the...
This paper is the continuation of the paper “Autour de nouvelles notions pour l'analyse des algorit...
AbstractWe introduce a formal framework for studying approximation properties of NP optimization (NP...
AbstractWe define a natural variant of NP, MAX NP, and also a subclass called MAX SNP. These are cla...
AbstractWe investigate the relationship between logical expressibility of NP optimization problems a...
AbstractThis paper presents the main results obtained in the field of approximation algorithms in a ...
AbstractWe investigate the relationship between logical expressibility of NP optimization problems a...
. In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibi...
AbstractWe present a reduction that allows us to establish completeness results for several approxim...
In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibili...
We study completeness in differential approximability classes. In differential approximation, the qu...
In this paper we deal with the class NCX of NP Optimization problems that are approximable within co...
We study completeness in differential approximability classes. In differential approximation, the qu...
We study completeness in differential approximability classes. In differential approximation, the qu...
We investigate the relationship between logical expressibility of NP optimization problems and thei...
The fact that polynomial time algorithm is very unlikely to be devised for an optimal solving of the...
This paper is the continuation of the paper “Autour de nouvelles notions pour l'analyse des algorit...
AbstractWe introduce a formal framework for studying approximation properties of NP optimization (NP...
AbstractWe define a natural variant of NP, MAX NP, and also a subclass called MAX SNP. These are cla...
AbstractWe investigate the relationship between logical expressibility of NP optimization problems a...
AbstractThis paper presents the main results obtained in the field of approximation algorithms in a ...
AbstractWe investigate the relationship between logical expressibility of NP optimization problems a...
. In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibi...
AbstractWe present a reduction that allows us to establish completeness results for several approxim...
In this paper we generalize the notion of polynomial-time approximation scheme preserving reducibili...
We study completeness in differential approximability classes. In differential approximation, the qu...
In this paper we deal with the class NCX of NP Optimization problems that are approximable within co...
We study completeness in differential approximability classes. In differential approximation, the qu...
We study completeness in differential approximability classes. In differential approximation, the qu...
We investigate the relationship between logical expressibility of NP optimization problems and thei...
The fact that polynomial time algorithm is very unlikely to be devised for an optimal solving of the...
This paper is the continuation of the paper “Autour de nouvelles notions pour l'analyse des algorit...