On cocolourings and cochromatic numbers of graphs
Discrete Applied Mathematics
Partitioning permutations into increasing and decreasing subsequences
Journal of Combinatorial Theory Series A
Smallest-last ordering and clustering and graph coloring algorithms
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
Approximating minimum cocolorings
Information Processing Letters
Approximating Maximum Edge Coloring in Multigraphs
APPROX '02 Proceedings of the 5th International Workshop on Approximation Algorithms for Combinatorial Optimization
SIAM Journal on Discrete Mathematics
Node-and edge-deletion NP-complete problems
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Partitioning chordal graphs into independent sets and cliques
Discrete Applied Mathematics - Brazilian symposium on graphs, algorithms and combinatorics
Graphs and Hypergraphs
Partitioning cographs into cliques and stable sets
Discrete Optimization
The maximum vertex coverage problem on bipartite graphs
Discrete Applied Mathematics
Fixed-parameter algorithms for the cocoloring problem
Discrete Applied Mathematics
Hi-index | 5.23 |
The (p, k)-coloring problems generalize the usual coloring problem by replacing stable sets by cliques and stable sets. Complexities of some variations of (p, k)-coloring problems (split-coloring and cocoloring) are studied in line graphs; polynomial algorithms or proofs of NP-completeness are given according to the complexity status. We show that the most general (p, k)-coloring problems are more difficult than the cocoloring and the split-coloring problems while there is no such relation between the last two problems. We also give complexity results for the problem of finding a maximum (p, k)-colorable subgraph in line graphs. Finally, upper bounds on the optimal values are derived in general graphs by sequential algorithms based on Welsh-Powell and Matula orderings.