lp-solve - 5.5.2.11-2 main

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.
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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.
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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.
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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.