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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Increasing the Antibandwidth of Sparse Matrices by a Genetic Algorithm
verfasst von : Petrica C. Pop, Oliviu Matei
Erschienen in: Recent Trends in Applied Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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The antibandwidth problem consists in finding a labeling of the vertices of a given undirected graph such that among all adjacent node pairs, the minimum difference between the node labels is maximized. In this paper, we formulate the antibandwidth problem in terms of matrices and propose an efficient genetic algorithm based heuristic approach for increasing the corresponding antibandwidth. We report computational results for a set of 30 benchmark instances. The preliminary results point out that our approach is an attractive and appropriate method to explore the solution space of this complex problem and leads to good solutions in reasonable computational times.