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A Genetic Programming Approach to the Matrix Bandwidth-Minimization Problem

机译:矩阵带宽最小化问题的一种遗传规划方法

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The bandwidth of a sparse matrix is the distance from the main diagonal beyond which all elements of the matrix are zero. The bandwidth minimisation problem for a matrix consists of finding the permutation of rows and columns of the matrix which ensures that the non-zero elements are located in as narrow a band as possible along the main diagonal. This problem, which is known to be NP-complete, can also be formulated as a vertex labelling problem for a graph whose edges represent the non-zero elements of the matrix. In this paper, a Genetic Programming approach is proposed and tested against two of the best-known and widely used bandwidth reduction algorithms. Results have been extremely encouraging.
机译:稀疏矩阵的带宽是距主对角线的距离,超过该距离,矩阵的所有元素均为零。矩阵的带宽最小化问题包括找到矩阵的行和列的排列,这确保了非零元素沿主对角线位于尽可能窄的频带中。这个已知为NP完全的问题也可以表述为图的顶点标记问题,该图的边缘表示矩阵的非零元素。在本文中,提出了一种遗传编程方法,并针对两种最著名且广泛使用的带宽减少算法进行了测试。结果非常令人鼓舞。

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