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Approximation Results for the Optimum Cost Chromatic Partition Problem
 J. Algorithms
"... . In this paper, we study the optimum cost chromatic partition (OCCP) problem for several graph classes. The OCCP problem is the problem of coloring the vertices of a graph such that adjacent vertices get different colors and that the total coloring costs are minimum. We prove several approximation ..."
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Cited by 26 (0 self)
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. In this paper, we study the optimum cost chromatic partition (OCCP) problem for several graph classes. The OCCP problem is the problem of coloring the vertices of a graph such that adjacent vertices get different colors and that the total coloring costs are minimum. We prove several approximation results for the OCCP problem restricted to bipartite, chordal, comparability, interval, permutation, split and unimodular graphs. We prove that there exists no polynomial approximation algorithm with ratio O(jV j 0:5 ) for the OCCP problem restricted to bipartite and interval graphs, unless P = NP . Furthermore, we propose approximation algorithms with ratio O(jV j 0:5 ) for bipartite, interval and unimodular graphs. Finally, we prove that there exists no polynomial approximation algorithm with ratio O(jV j 1 ) for the OCCP problem restricted to split, chordal, permutation and comparability graphs, unless P = NP .
Precoloring Extension With Fixed Color Bound
, 1994
"... . Precoloring Extension (shortly PrExt) is the following problem: Given a graph G with some precolored vertices and a color bound k, can the precoloring of G be extended to a proper coloring of all vertices of G using not more than k colors? Answering an open problem from [6], we prove that PrExt ..."
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Cited by 15 (1 self)
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. Precoloring Extension (shortly PrExt) is the following problem: Given a graph G with some precolored vertices and a color bound k, can the precoloring of G be extended to a proper coloring of all vertices of G using not more than k colors? Answering an open problem from [6], we prove that PrExt with fixed color bound k = 3 is NPcomplete for bipartite (and even planar) graphs, and we prove a general result on parametrized PrExt. We also give a simplified argument why PrExt with fixed color bound is solvable in polynomial time for graphs of bounded treewidth (and hence also for chordal graphs). 1. Introduction and Statement of the Results All graphs considered are finite, undirected and without loops or multiple edges. A coloring of a graph is any mapping from its vertex set into a set of colors, a coloring is proper if adjacent vertices are mapped onto distinct colors. The following decision problem is introduced in [1] and studied in [6, 7, 8]: Precoloring Extension (short...
On the complexity of the Maximum Cut problem
 Nordic Journal of Computing
, 1991
"... The complexity of the simple maxcut problem is investigated for several special classes of graphs. It is shown that this problem is NPcomplete when restricted to one of the following classes: chordal graphs, undirected path graphs, split graphs, tripartite graphs, and graphs that are the complement ..."
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Cited by 14 (4 self)
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The complexity of the simple maxcut problem is investigated for several special classes of graphs. It is shown that this problem is NPcomplete when restricted to one of the following classes: chordal graphs, undirected path graphs, split graphs, tripartite graphs, and graphs that are the complement of a bipartite graph. The problem can be solved in polynomial time, when restricted to graphs with bounded treewidth, or cographs. We also give large classes of graphs that can be seen as generalizations of classes of graphs with bounded treewidth and of the class of the cographs, and allow polynomial time algorithms for the simple max cut problem. 1 Introduction One of the best known combinatorial graph problems is the max cut problem. In this problem, we have a weighted, undirected graph G = (V; E) and we look for a partition of the vertices of G into two disjoint sets, such that the total weight of the edges that go from one set to the other is as large as possible. In the simple max cu...