Reducing the Bandwidth of a Sparse Matrix with Tabu Search
R. Martí, M. Laguna, F. Glover and V. Campos
European Journal of Operational Research, vol. 135, no. 2, pp. 211-220
(2001)

Abstract
The bandwidth of a matrix A={a(i,j)} is defined as the maximum
absolute difference between i and j for which a(i,j) is different than
zero . The problem of reducing the bandwidth of a matrix consists
of finding a permutation of the rows and columns that keeps the nonzero
elements in a band that is as close as possible to the main diagonal of
the matrix. This NP-complete problem can also be formulated as a
labeling of vertices on a graph, where edges are the nonzero elements of
the corresponding symmetrical matrix. Many bandwidth reduction algorithms
have been developed since the 1960s and applied to structural engineering,
fluid dynamics and network analysis. For the most part, these procedures
do not incorporate metaheuristic elements, which is one of the main goals
of our current development. Another equally important goal is to
design and test a special type of candidate list strategy to be embedded
in a tabu search procedure for the bandwidth reduction problem. This
candidate list strategy accelerates the selection of a move in the neighborhood
of the current solution in any given iteration. Our extensive experimentation
shows that the proposed procedure outperforms the best-known algorithms
in terms of solution quality consuming a reasonable computational effort.

Full text