CGAL 5.4.4  Linear and Quadratic Programming Solver

MPS is a commonly used file format for storing linear and quadratic programs according to the concepts QuadraticProgram
, LinearProgram
, NonnegativeQuadraticProgram
, and NonnegativeLinearProgram
, see also https://en.wikipedia.org/wiki/MPS_(format)
.
CGAL supports a large subset of this format, but there are MPS files around that we cannot read (for example, files that encode integrality constraints on the variables). Also, there might be some other MPSbased solvers that will not be able to read the MPS files written by CGAL, since we do not strictly adhere to the very rigid layout requirements of the original MPS format.
Let's look at an example first. The quadratic program
\[ \begin{array}{lrcl} \mbox{minimize} & x^2 + 4(y4)^2 &(=& x^2 + 4y^2  32y + 64) \\ \mbox{subject to} & x + y &\leq& 7 \\ & x + 2y &\leq& 4 \\ & x &\geq& 0 \\ & y &\geq& 0 \\ & y &\leq& 4 \end{array} \]
has the following description in MPS format.
NAME first_qp ROWS N obj L c0 L c1 COLUMNS x0 c0 1 x0 c1 1 x1 obj 32 x1 c0 1 x1 c1 2 RHS rhs obj 64 rhs c0 7 rhs c1 4 BOUNDS UP BND x1 4 QMATRIX x0 x0 2 x1 x1 8
Here comes a semiformal description of the format in general.
NAME Section
This (mandatory) section consists of a single line starting with NAME
. Everything starting from the first nonwhitespace after that until the end of the line constitutes the name of the problem.
ROWS Section
In the (mandatory) ROW
section, you find one line for every constraint, where the letter L
indicates relation \( \leq\), letter G
stands for \( \geq\), and E
for \( =\). In addition, there is a row for the linear objective function (indicated by letter N
). In that section, names are asigned to the constraints (here: c0, c1
) and the objective function (here: obj
). An MPS file may encode several linear objective functions by using several rows starting with N
, but we ignore all but the first.
COLUMNS Section
The (mandatory) COLUMNS
section encodes the constraint matrix \( A\) and the linear objective function vector \( c\). Every line consists of one or two sequences of three tokens \( j i val\), where \( j\) is the name of a variable (here, we have variables x0,x1
), \( i\) is the name of a constraint or the objective function, and \( val\) is the value \( A_{ij}\) (if \( i\) names a constraint), or \( c_j\) (if \( i\) names the linear objective function). Values for pairs \( (i,j)\) that are not specified in this section default to \( 0\). Otherwise, for every pair \( (i,j)\), the last specified value determines \( A_{ij}\) or \( c_j\).
RHS Section
This (mandatory) section encodes the righthand side vector \( b\) and the constant term \( c_0\) in the objective function. The first token in every line is an identifier (here: rhs
). An MPS file may encode several righthand sides \( b\) by using several such identifiers, but we ignore all lines having an identifier different from that of the first line.
The righthand side identifier is succeeded by one or two sequences of tokens \( i val\), where \( i\) names a constraint or the linear objective function, and \( val\) specifies the value \( b_i\) (if \( i\) names a constraint), or \( c_0\) (if \( i\) names the linear objective function). Values that are not specified in this section default to \( 0\). Otherwise, for every \( i\), the last specified value determines \( b_{i}\) or \( c_0\).
BOUNDS Section
This (optional) section encodes the lower and upper bound vectors \( l\) and \( u\) for the variables. The default bounds for any variable \( x_j\) are \( 0\leq x_j\leq \infty\); the BOUNDS
section is used to override these defaults. In particular, if there is no BOUNDS
section, the program is nonnegative and actually a model of the concept NonnegativeQuadraticProgram
or NonnegativeLinearProgram
.
The first token in every line is succeeded by an (optional) identifier (here: BND
). An MPS file may encode several bound vectors \( l\) and \( u\) by using several such identifiers, but we ignore all lines having an identifier different from that of the first line. The first token \( t\) itself determines the type of the bound, and the token \( j\) after the bound identifier names the variable to which the bound applies In case of bound types FX
, LO
, and UP
, there is another token \( val\) that specifices the bound value. Here is how bound type and value determine a bound for variable \( x_j\). There may be several bound specifications for a single variable, and they are processed in order of appearance.
bound type  resulting bound 

FX  \(x_j = val\) ( \(x_j\) becomes a fixed variable) 
LO  \(x_j \geq val\) (upper bound remains unchanged) 
UP  \(x_j \leq val\) (lower bound remains unchanged, except if \(val<0\); then, a zero lower bound is reset to \(\infty\)) 
FR  \(\infty \leq x_j\leq\infty\) (previous bounds are discarded) 
MI  \(x_j\geq \infty\) (upper bound remains unchanged) 
PL  \(x_j\leq \infty\) (lower bound remains unchanged) 
QMATRIX / QUADOBJ / DMATRIX Section
This (optional) section encodes the quadratic objective function matrix \( D\). Every line is a sequence \( i j val\) of three tokens, where both \( i\) and \( j\) name variables, and \( val\) is the value \( 2D_{i,j}\) (in case of QMATRIX
or QUADOBJ
), or \( D_{ij}\) (in case of DMATRIX
).
In case of QMATRIX
and DMATRIX
, all nonzero entries must be specified: if there is a line \( i j val\), then there must also be a line \( j i val\), since \( D\) is required to be symmetric. In case of QUADOBJ
, only the entries of \( 2D\) on or below the diagonal must be specified, entries above the diagonal are deduced from symmetry. It is not allowed to specify two or more different nonzero values for an unordered pair \( \{i,j\}\).
If this section is missing or does not contain nonzero values, the program is a model of the concept LinearProgram
.
Miscellaneous
Our MPS format also supports an (optional) RANGES
section, but we don't explain this here.
CGAL::Quadratic_program_from_mps<NT>