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lp-solve package

lp-solve 5.5.0.13-7build2 source package in Ubuntu

Changelog

lp-solve (5.5.0.13-7build2) xenial; urgency=medium

  * No-change rebuild against suitesparse 1:4.4.5-2

 -- Graham Inggs <email address hidden>  Tue, 01 Dec 2015 16:50:15 +0200

Upload details

Uploaded by:
Graham Inggs
Sponsored by:
Sebastien Bacher
Uploaded to:
Xenial
Original maintainer:
Juan Esteban Monsalve Tobon
Architectures:
any all
Section:
math
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Xenial release main math

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File Size SHA-256 Checksum
lp-solve_5.5.0.13.orig-docs.tar.gz 369.6 KiB 1d31b9b16f914372bc0e58c279fefabca279f3b665f21be8d83b418addd75509
lp-solve_5.5.0.13.orig.tar.gz 774.8 KiB 8714793ffc227c5d78b83acc8e409a68f6159d83bcf0af632a69887c97fe4155
lp-solve_5.5.0.13-7build2.debian.tar.xz 8.6 KiB 13aef03eeb087a8ef90f4c2b0e92252f8b06f5996d94776fe9ed7f2192875de9
lp-solve_5.5.0.13-7build2.dsc 1.6 KiB a1cc1033f91c8e1d7661c011eeef703fa74eeb4929fbf4272c0f46d64d1d5ec9

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Binary packages built by this source

liblpsolve55-dev: Solve (mixed integer) linear programming problems - library

 The linear programming (LP) problem can be formulated as: Solve A.x >=
 V1, with V2.x maximal. A is a matrix, x is a vector of (nonnegative)
 variables, V1 is a vector called the right hand side, and V2 is a vector
 specifying the objective function.
 .
 An integer linear programming (ILP) problem is an LP with the
 constraint that all the variables are integers. In a mixed integer
 linear programming (MILP) problem, some of the variables are integer
 and others are real.
 .
 The program lp_solve solves LP, ILP, and MILP problems. It is slightly
 more general than suggested above, in that every row of A (specifying
 one constraint) can have its own (in)equality, <=, >= or =. The result
 specifies values for all variables.
 .
 lp_solve uses the 'Simplex' algorithm and sparse matrix methods for
 pure LP problems. If one or more of the variables is declared
 integer, the Simplex algorithm is iterated with a branch and bound
 algorithm, until the desired optimal solution is found. lp_solve can
 read MPS format input files.
 .
 This package contains the static library for developing programs using
 liblpsolve.
 .
 Homepage http://www.geocities.com/lpsolve/

lp-solve: Solve (mixed integer) linear programming problems

 The linear programming (LP) problem can be formulated as: Solve A.x >=
 V1, with V2.x maximal. A is a matrix, x is a vector of (nonnegative)
 variables, V1 is a vector called the right hand side, and V2 is a vector
 specifying the objective function.
 .
 An integer linear programming (ILP) problem is an LP with the
 constraint that all the variables are integers. In a mixed integer
 linear programming (MILP) problem, some of the variables are integer
 and others are real.
 .
 The program lp_solve solves LP, ILP, and MILP problems. It is slightly
 more general than suggested above, in that every row of A (specifying
 one constraint) can have its own (in)equality, <=, >= or =. The result
 specifies values for all variables.
 .
 lp_solve uses the 'Simplex' algorithm and sparse matrix methods for
 pure LP problems. If one or more of the variables is declared
 integer, the Simplex algorithm is iterated with a branch and bound
 algorithm, until the desired optimal solution is found. lp_solve can
 read MPS format input files.
 .
 Homepage http://www.geocities.com/lpsolve/

lp-solve-doc: Solve (mixed integer) linear programming problems - documentation

 The linear programming (LP) problem can be formulated as: Solve A.x >=
 V1, with V2.x maximal. A is a matrix, x is a vector of (nonnegative)
 variables, V1 is a vector called the right hand side, and V2 is a vector
 specifying the objective function.
 .
 An integer linear programming (ILP) problem is an LP with the
 constraint that all the variables are integers. In a mixed integer
 linear programming (MILP) problem, some of the variables are integer
 and others are real.
 .
 The program lp_solve solves LP, ILP, and MILP problems. It is slightly
 more general than suggested above, in that every row of A (specifying
 one constraint) can have its own (in)equality, <=, >= or =. The result
 specifies values for all variables.
 .
 lp_solve uses the 'Simplex' algorithm and sparse matrix methods for
 pure LP problems. If one or more of the variables is declared
 integer, the Simplex algorithm is iterated with a branch and bound
 algorithm, until the desired optimal solution is found. lp_solve can
 read MPS format input files.
 .
 This package contains the documentation for the lp_solve program and
 the library.
 .
 Homepage http://www.geocities.com/lpsolve/