MPS (.mps)
- Import fully supports the MPS format.
Background & Context
-
- MPS mathematical file format.
- De facto standard for specifying linear programming (LP) problems.
- Commonly used as input format by LP solvers.
- MPS is an acronym for Mathematical Programming System.
- Plain text ASCII format, sometimes compressed as binary.
- Stores data in a fixed-width tabular form.
- Developed in the 1970s at IBM.
Import
- Import["file.mps"] imports an MPS file, returning an expression representing an optimization problem.
- Import["file.mps"] returns a list of objective functions and constraints in a form suitable as input for NMinimize.
- Import["file.mps",elem] imports the specified element from an MPS file.
- Import["file.mps",{elem,suba,subb,…}] imports a subelement.
- Import["file.mps",{{elem1,elem2,…}}] imports multiple elements.
- The import format can be specified with Import["file", "MPS"] or Import["file",{"MPS",elem,…}].
- See the following reference pages for full general information:
-
Import import from a file CloudImport import from a cloud object ImportString import from a string ImportByteArray import from a byte array
Import Elements
- General Import elements:
-
"Elements" list of elements and options available in this file "Summary" summary of the file "Rules" list of rules for all available elements - Data representation elements:
-
"Equations" list of objective functions and constraints "LinearOptimizationData" vectors and matrices representing a linear program "ConstraintMatrix" matrix describing the constraints of a linear optimization problem - Import uses the "Equations" element by default.
Examples
Basic Examples (3)
Get a list of Import elements from an MPS file:
Read an MPS file as a list of objective functions and constraints that is an expression suitable for LinearOptimization or NMinimize:
Use it as input for LinearOptimization:
Use it as input for NMinimize:
Read MPS data in a form suitable as input for LinearOptimization:
Use it as input for LinearOptimization:
Import and plot the constraint matrix of the previous example: