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ngraph.sparse-collection

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Subset of the University of Florida sparse matrix collection

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# LPnetlib/lp_fit1d UF Sparse Matrix Collection, Tim Davis http://www.cise.ufl.edu/research/sparse/matrices/LPnetlib/lp_fit1d [Netlib LP problem fit1d: minimize c'*x, where Ax=b, lo<=x<=hi] id: 624 date: 1990 author: R. Fourer ed: R. Fourer fields: title name A b id aux kind date author ed notes aux: c lo hi z0 kind: linear programming problem notes: A Netlib LP problem, in lp/data. For more information send email to netlib@ornl.gov with the message: send index from lp send readme from lp/data The following are relevant excerpts from lp/data/readme (by David M. Gay): The column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude slack and surplus columns and the right-hand side vector, but include the cost row. We have omitted other free rows and all but the first right-hand side vector, as noted below. The byte count is for the MPS compressed file; it includes a newline character at the end of each line. These files start with a blank initial line intended to prevent mail programs from discarding any of the data. The BR column indicates whether a problem has bounds or ranges: B stands for "has bounds", R for "has ranges". The BOUND-TYPE TABLE below shows the bound types present in those problems that have bounds. The optimal value is from MINOS version 5.3 (of Sept. 1988) running on a VAX with default options. PROBLEM SUMMARY TABLE Name Rows Cols Nonzeros Bytes BR Optimal Value FIT1D 25 1026 14430 51734 B -9.1463780924E+03 BOUND-TYPE TABLE FIT1D UP Supplied by Bob Fourer. When included in Netlib: Cost coefficients negated. Concerning FIT1D, FIT1P, FIT2D, FIT2P, Bob Fourer says The pairs FIT1P/FIT1D and FIT2P/FIT2D are primal and dual versions of the same two problems [except that we have negated the cost coefficients of the dual problems so all are minimization problems]. They originate from a model for fitting linear inequalities to data, by minimization of a sum of piecewise-linear penalties. The FIT1 problems are based on 627 data points and 2-3 pieces per primal pl penalty term. The FIT2 problems are based on 3000 data points (from a different sample altogether) and 4-5 pieces per pl term. Added to Netlib on 31 Jan. 1990 ![LPnetlib/lp_fit1d](http://yifanhu.net/GALLERY/GRAPHS/GIF_SMALL/LPnetlib@lp_fit1d.gif)