2003 | OriginalPaper | Buchkapitel
Integrated Genetic Algorithm with Hill Climbing for Bandwidth Minimization Problem
verfasst von : Andrew Lim, Rodrigues Brian, Fei Xiao
Erschienen in: Genetic and Evolutionary Computation — GECCO 2003
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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In this paper, we propose an integrated Genetic Algorithm with Hill Climbing to solve the matrix bandwidth minimization problem, which is to reduce bandwidth by permuting rows and columns resulting in the nonzero elements residing in a band as close as possible to the diagonal. Experiments show that this approach achieves the best solution quality when compared with the GPS [1] algorithm, Tabu Search [3], and the GRASP with Path Relinking methods [4], while being faster than the latter two newly-developed heuristics.