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Titlebook: Numerical Analysis; Proceedings of the D G. Alistair Watson Conference proceedings 1976 Springer-Verlag Berlin Heidelberg 1976 Numerische M

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樓主
發(fā)表于 2025-3-21 20:10:00 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Numerical Analysis
副標(biāo)題Proceedings of the D
編輯G. Alistair Watson
視頻videohttp://file.papertrans.cn/669/668924/668924.mp4
叢書名稱Lecture Notes in Mathematics
圖書封面Titlebook: Numerical Analysis; Proceedings of the D G. Alistair Watson Conference proceedings 1976 Springer-Verlag Berlin Heidelberg 1976 Numerische M
出版日期Conference proceedings 1976
關(guān)鍵詞Numerische Mathematik; calculus; differential equation; finite element method; numerical analysis
版次1
doihttps://doi.org/10.1007/BFb0080109
isbn_softcover978-3-540-07610-0
isbn_ebook978-3-540-38129-7Series ISSN 0075-8434 Series E-ISSN 1617-9692
issn_series 0075-8434
copyrightSpringer-Verlag Berlin Heidelberg 1976
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 21:41:32 | 只看該作者
Solution of linear complementarity problems by linear programming,iagonal elements.) Included in this class are other matrices such as nonnegative matrices with a strictly dominant diagonal and matrices that are the sum of a Z-matrix having a nonnegative inverse and the tensor product of any two positive vectors in R..
板凳
發(fā)表于 2025-3-22 02:34:37 | 只看該作者
Sparse in-core linear programming,gorithm is practical. This algorithm has long been known to give good results in respect of number of iterations, but has been thought to be impractical..Test results on genuine problems with hundreds of rows and thousands of columns will be reported. These tests include comparisons with other methods.
地板
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Solution of linear complementarity problems by linear programming,is a given n x 1 vector. In this paper the class of matrices M for which this problem is solvable by a single linear program is enlarged to include matrices other than those that are z-matrices or those that have an inverse which is a z-matrix. (A Z-matrix is real square matrix with nonpositive offd
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發(fā)表于 2025-3-23 09:12:09 | 只看該作者
Sparse in-core linear programming,l-adapted to sparsity preservation, being capable of revising the factorisation without any fill-in whenever this is possible by permutations alone. In addition strategies for colum pivoting in the simplex method itself will be discussed and in particular it will be shown that the “steepest edge” al
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