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lp-solve package

lp-solve 5.5.2.5-2build2 source package in Ubuntu

Changelog

lp-solve (5.5.2.5-2build2) jammy; urgency=high

  * No change rebuild for ppc64el baseline bump.

 -- Julian Andres Klode <email address hidden>  Thu, 24 Mar 2022 17:24:58 +0100

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Uploaded by:
Julian Andres Klode
Uploaded to:
Jammy
Original maintainer:
Ubuntu Developers
Architectures:
any all
Section:
math
Urgency:
Very Urgent

See full publishing history Publishing

Series Pocket Published Component Section
Lunar release main math
Kinetic release main math
Jammy release main math

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File Size SHA-256 Checksum
lp-solve_5.5.2.5.orig-doc.tar.gz 1.4 MiB 4c6085a7083cca04c18876a1c8838ae2427b97080219fffedde1c3a96bc13561
lp-solve_5.5.2.5.orig.tar.gz 793.9 KiB 201a7c62b8b3360c884ee2a73ed7667e5716fc1e809755053b398c2f5b0cf28a
lp-solve_5.5.2.5-2build2.debian.tar.xz 16.1 KiB 5c3cc83e826cbb72cd094c96fa1337ef2984e24a5a01605bc2b87c0fd7aabf42
lp-solve_5.5.2.5-2build2.dsc 2.3 KiB 5dd558a608e22e0fa495a0fd425e7b00f082736de7085c789b61c634f9bd2e80

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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.

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.

lp-solve-dbgsym: debug symbols for lp-solve
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.