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Variable neighbourhood search for bandwidth reduction
Authors:Nenad Mladenovic  Dragan Urosevic  Dionisio Pérez-Brito  Carlos G García-González
Institution:1. School of Mathematics, Brunel University – West London, UK;2. Mathematical Institute SANU Belgrade, Serbia;3. Dpto. de Estadística, Investigación Operativa y Computación, Universidad de La Laguna, Spain;4. Dpto. de Economía de las Instituciones, Estadística Económica y Econometría, Universidad de La Laguna, Spain
Abstract:The problem of reducing the bandwidth of a matrix consists of finding a permutation of rows and columns of a given matrix which keeps the non-zero elements in a band as close as possible to the main diagonal. This NP-complete problem can also be formulated as a vertex labelling problem on a graph, where each edge represents a non-zero element of the matrix. We propose a variable neighbourhood search based heuristic for reducing the bandwidth of a matrix which successfully combines several recent ideas from the literature. Empirical results for an often used collection of 113 benchmark instances indicate that the proposed heuristic compares favourably to all previous methods. Moreover, with our approach, we improve best solutions in 50% of instances of large benchmark tests.
Keywords:Combinatorial optimization  Matrix bandwidth minimization  Metaheuristics  Variable neighbourhood search
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