Deprecated in favor of MathOptFormat.
MPSReader is a Julia package that transform a .mps file (MPS format) into a model using JuMP.
The MPS format represents problem of the following form :
optimize cᵀ x + c₀
subject to L ≤ Ax ≤ U
l ≤ x ≤ u
optimize stands for minimize or maximize, MPSReader will use minimize as default but it can be specified in Free MPS Format. c₀ ∈ ℝ is a constant term and c ∈ ℝⁿ is the cost function.
L and U are vectors of constraints bounds. By default the lower bound of a constraint is -Inf and the upper bound is +Inf. l and u are vectors of bounds of x. By default the lower bound of a variable is 0 and the upper bound is +Inf. x can have simultaneously binary elements, integer elements and continuous elements. Semi-continuous variables are not supported and using MPSReader on a file containing it will throw an error.
This package exports 2 functions: readmps() and mpstomodel()
julia 1.0.0
MathOptInterface v0.8.1
JuMP v0.19.0
LinearAlgebra
If you are using julia 1.0.0 or newer you can install all the needed package as follow:
julia> using Pkg
julia> Pkg.add("MathOptInterface")
julia> Pkg.add("LinearAlgebra")
julia> Pkg.develop("JuMP")TODO
julia> include("examples/test.jl")You should get 7 JuMP models and the expected output is in examples/Test_output.txt
julia> fixed = true #false
julia> varTypes, bounds, objsense, c, c0, A, b, conTypes = readmps("mympsfile.mps", fixed)
julia> myModel, myVariables = mpstomodel("mympsfile.mps", mySolver, fixed) # mySolver = GLPK.OptimizervarTypes is a vector of booleans, elements are true if the variable is continuous and at false if it is an integer or a boolean. bounds is a vector of pairs, the first is the lower bound of the variable and the second the upper bound. objsense is a Symbol for the optimizing sense, (:min by default). conTypes is a vector that gives the type of the constraint, 1 for ≤, 2 for = and 3 for ≥. Each constraint having a lower and an upper bound is duplicated into a constraint with a lower bound and another with an upper bound.
myModel is the model in minimization (maximization) with constraints of type ≥ (≤) and =. Therefore it should have this form:
minimize cᵀ x + c₀
subject to Ax ≥ b
Aeq x = beq
l ≤ x ≤ u
or
maximize cᵀ x + c₀
subject to Ax ≤ b
Aeq x = beq
l ≤ x ≤ u
By default fixed is true but if you are using a Free MPS Format you can set fixed variable to false. As lpsolve authors we suggest to try the fixed format and if it fails switch for the free format.
- MIPLIB: https://miplib.zib.de/
- MPS file format: https://lpsolve.sourceforge.net/5.5/mps-format.htm