Fast heuristics for the edge coloring of large graphs

Fast heuristics for the edge coloring of large graphs

Heuristic algorithms for coloring the edges of large undirected single-edge graphs with (or very close to) the minimal number of colors are presented. Compared to simulated annealing and a grouping genetic algorithm for small graphs, the heuristics were not only faster by orders of magnitude, but al...

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Hauptverfasser: Hilgemeier, M., Drechsler, N., Drechsler, R.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Color
Computational modeling
Computer science
Evolutionary computation
Genetic algorithms
Heuristic algorithms
Optical design
Optical fiber networks
Simulated annealing
Very large scale integration
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Beschreibung
Zusammenfassung:Heuristic algorithms for coloring the edges of large undirected single-edge graphs with (or very close to) the minimal number of colors are presented. Compared to simulated annealing and a grouping genetic algorithm for small graphs, the heuristics were not only faster by orders of magnitude, but almost all solutions had the optimal color number; the rest differed by at most two colors. For large graphs, the heuristics were validated by an evolutionary algorithm. Here, the heuristics often found an optimum or a solution very close to it.
DOI:10.1109/DSD.2003.1231932