NAG C Library Function Document
nag_opt_miqp_mps_read (e04mxc)
1
Purpose
nag_opt_miqp_mps_read (e04mxc) reads data for sparse linear programming, mixed integer linear programming, quadratic programming or mixed integer quadratic programming problems from an external file which is in standard or compatible MPS input format.
2
Specification
#include <nag.h> 
#include <nage04.h> 
void 
nag_opt_miqp_mps_read (Nag_FileID fileid,
Integer maxn,
Integer maxm,
Integer maxnnz,
Integer maxncolh,
Integer maxnnzh,
Integer maxlintvar,
Integer mpslst,
Integer *n,
Integer *m,
Integer *nnz,
Integer *ncolh,
Integer *nnzh,
Integer *lintvar,
Integer *iobj,
double a[],
Integer irowa[],
Integer iccola[],
double bl[],
double bu[],
char pnames[][9],
Integer *nname,
char crname[][9],
double h[],
Integer irowh[],
Integer iccolh[],
Integer *minmax,
Integer intvar[],
NagError *fail) 

3
Description
nag_opt_miqp_mps_read (e04mxc) reads data for linear programming (LP) or quadratic programming (QP) problems (or their mixed integer variants) from an external file which is prepared in standard or compatible MPS (see
IBM (1971)) input format. It then initializes
$n$ (the number of variables),
$m$ (the number of general linear constraints), the
$m$ by
$n$ matrix
$A$, the vectors
$l$,
$u$,
$c$ (stored in row
iobj of
$A$) and the
$n$ by
$n$ Hessian matrix
$H$ for use with
nag_opt_sparse_convex_qp_solve (e04nqc).
This function is
designed to solve problems of the form
The input file of data may only contain two types of lines:
1. 
Indicator lines (specifying the type of data which is to follow). 
2. 
Data lines (specifying the actual data). 
A
section is a combination of an indicator line and its corresponding data line(s). Any characters beyond column 80 are ignored. Indicator lines must not contain leading blank characters (in other words they must begin in column 1). The following displays the order in which the indicator lines must appear in the file:
NAME 
usersupplied name 
(optional) 
OBJSENSE 
(optional) 

data line 
OBJNAME 
(optional) 

data line 
ROWS 

data line(s) 
COLUMNS 

data line(s) 
RHS 

data line(s) 
RANGES 
(optional) 

data line(s) 
BOUNDS 
(optional) 

data line(s) 
QUADOBJ 
(optional) 

data line(s) 
ENDATA 
A data line follows a fixed format, being made up of fields as defined below. The contents of the fields may have different significance depending upon the section of data in which they appear.

Field 1 
Field 2 
Field 3 
Field 4 
Field 5 
Field 6 
Columns 
$2\u20133$ 
$5\u201312$ 
$15\u201322$ 
$25\u201336$ 
$40\u201347$ 
$50\u201361$ 
Contents 
Code 
Name 
Name 
Value 
Name 
Value 
Each name and code must consist of ‘printable’ characters only; names and codes supplied must match the case used in the following descriptions. Values are read using a field width of $12$. This allows values to be entered in several equivalent forms. For example, $1.2345678$, $\text{1.2345678e+0}$, $\text{123.45678e\u22122}$ and $\text{12345678e\u221207}$ all represent the same number. It is safest to include an explicit decimal point.
Lines with an asterisk ($*$) in column $1$ will be considered comment lines and will be ignored by the function.
Columns outside the six fields must be blank, except for columns 72–80, whose contents are ignored by the function. A nonblank character outside the predefined six fields and columns 72–80 is considered to be a major error (
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_MPS_ILLEGAL_DATA_LINE; see
Section 6), unless it is part of a comment.
3.1.1
NAME Section (optional)
The NAME section is the only section where the data must be on the same line as the indicator. The ‘usersupplied name’ must be in field
$3$ but may be blank.
Field 
Required 
Description 
$3$ 
No 
Name of the problem 
3.1.2
OBJSENSE Section (optional)
The data line in this section can be used to specify the sense of the objective function. If this section is present it must contain only one data line. If the section is missing or empty, minimization is assumed.
Field 
Required 
Description 
$2$ 
No 
Sense of the objective function 
Field 2 may contain either MIN, MAX, MINIMIZE or MAXIMIZE.
3.1.3
OBJNAME Section (optional)
The data line in this section can be used to specify the name of a free row (see
Section 3.1.4) that should be used as the objective function. If this section is present it must contain only one data line. If the section is missing or is empty, the first free row will be chosen instead. Alternatively, OBJNAME can be overridden by setting nonempty
${\mathbf{pnames}}\left[1\right]$ (see
Section 5).
Field 
Required 
Description 
$2$ 
No 
Row name to be used as the objective function 
Field 2 must contain a valid row name.
3.1.4
ROWS Section
The data lines in this section specify unique row (constraint) names and their inequality types (i.e., unconstrained,
$=$,
$\ge $ or
$\le $).
Field 
Required 
Description 
$1$ 
Yes 
Inequality key 
$2$ 
Yes 
Row name 
The inequality key specifies each row's type. It must be
E,
G,
L or
N and can be in either column
$2$ or
$3$.
Inequality Key 
Description 
$\mathit{l}$ 
$\mathit{u}$ 
N 
Free row 
$\infty $ 
$\infty $ 
G 
Greater than or equal to 
finite 
$\infty $ 
L 
Less than or equal to 
$\infty $ 
finite 
E 
Equal to 
finite 
$l$ 
Row type
N stands for ‘Not binding’. It can be used to define the objective row. The objective row is a free row that specifies the vector
$c$ in the linear objective term
${c}^{\mathrm{T}}x$. If there is more than one free row, the first free row is chosen, unless another free row name is specified by OBJNAME (see
Section 3.1.3) or
${\mathbf{pnames}}\left[1\right]$ (see
Section 5). Note that
$c$ is assumed to be zero if either the chosen row does not appear in the COLUMNS section (i.e., has no nonzero elements) or there are no free rows defined in the ROWS section.
3.1.5
COLUMNS Section
Data lines in this section specify the names to be assigned to the variables (columns) in the general linear constraint matrix
$A$, and define, in terms of column vectors, the actual values of the corresponding matrix elements.
Field 
Required 
Description 
$2$ 
Yes 
Column name 
$3$ 
Yes 
Row name 
$4$ 
Yes 
Value 
$5$ 
No 
Row name 
$6$ 
No 
Value 
Each data line in the COLUMNS section defines the nonzero elements of $A$ or $c$. Any elements of $A$ or $c$ that are undefined are assumed to be zero. Nonzero elements of $A$ must be grouped by column, that is to say that all of the nonzero elements in the jth column of $A$ must be specified before those in the $\mathit{j}+1$th column, for $\mathit{j}=1,2,\dots ,n1$. Rows may appear in any order within the column.
3.1.5.1
Integer Markers
For backward compatibility
nag_opt_miqp_mps_read (e04mxc) allows you to define the integer variables within the COLUMNS section using integer markers, although this is not recommended as markers can be treated differently by different MPS readers; you should instead define any integer variables in the BOUNDS section (see below). Each marker line must have the following format:
Field 
Required 
Description 
$2$ 
No 
Marker ID 
$3$ 
Yes 
Marker tag 
$5$ 
Yes 
Marker type 
The marker tag must be ${}^{\prime}$MARKER${}^{\prime}$. The marker type must be ${}^{\prime}$INTORG${}^{\prime}$ to start reading integer variables and ${}^{\prime}$INTEND${}^{\prime}$ to finish reading integer variables. This implies that a row cannot be named ${}^{\prime}$MARKER${}^{\prime}$, ${}^{\prime}$INTORG${}^{\prime}$ or ${}^{\prime}$INTEND${}^{\prime}$. Please note that both marker tag and marker type comprise of $8$ characters as a ${}^{\prime}$ is the mandatory first and last character in the string. You may wish to have several integer marker sections within the COLUMNS section, in which case each marker section must begin with an ${}^{\prime}$INTORG${}^{\prime}$ marker and end with an ${}^{\prime}$INTEND${}^{\prime}$ marker and there should not be another marker between them.
Field 2 is ignored by nag_opt_miqp_mps_read (e04mxc). When an integer variable is declared it will keep its default bounds unless they are changed in the BOUNDS section. This may vary between different MPS readers.
3.1.6
RHS Section
This section specifies the righthand side values (if any) of the general linear constraint matrix
$A$.
Field 
Required 
Description 
$2$ 
Yes 
RHS name 
$3$ 
Yes 
Row name 
$4$ 
Yes 
Value 
$5$ 
No 
Row name 
$6$ 
No 
Value 
The MPS file may contain several RHS sets distinguished by RHS name. If an RHS name is defined in
${\mathbf{pnames}}\left[2\right]$ (see
Section 5) then
nag_opt_miqp_mps_read (e04mxc) will read in only that RHS vector, otherwise the first RHS set will be used.
Only the nonzero RHS elements need to be specified. Note that if an RHS is given to the objective function it will be ignored by nag_opt_miqp_mps_read (e04mxc). An RHS given to the objective function is dealt with differently by different MPS readers, therefore it is safer to not define an RHS of the objective function in your MPS file. Note that this section may be empty, in which case the RHS vector is assumed to be zero.
3.1.7
RANGES Section (optional)
Ranges are used to modify the interpretation of constraints defined in the ROWS section (see
Section 3.1.4) to the form
$l\le Ax\le u$, where both
$l$ and
$u$ are finite. The range of the constraint is
$r=ul$.
Field 
Required 
Description 
$2$ 
Yes 
Range name 
$3$ 
Yes 
Row name 
$4$ 
Yes 
Value 
$5$ 
No 
Row name 
$6$ 
No 
Value 
The range of each constraint implies an upper and lower bound dependent on the inequality key of each constraint, on the RHS
$b$ of the constraint (as defined in the RHS section), and on the range
$r$.
Inequality Key 
Sign of $\text{}\mathit{r}$ 
$\mathit{l}$ 
$\mathit{u}$ 
E 
$+$ 
$b$ 
$b+r$ 
E 
$$ 
$b+r$ 
$b$ 
G 
$+/$ 
$b$ 
$b+\leftr\right$ 
L 
$+/$ 
$b\leftr\right$ 
$b$ 
N 
$+/$ 
$\infty $ 
$+\infty $ 
If a range name is defined in
${\mathbf{pnames}}\left[3\right]$ (see
Section 5) then the function will read in only the range set of that name, otherwise the first set will be used.
3.1.8
BOUNDS Section (optional)
These lines specify limits on the values of the variables (the quantities
$l$ and
$u$ in
$l\le x\le u$). If a variable is not specified in the bound set then it is automatically assumed to lie between
$0$ and
$+\infty $.
Field 
Required 
Description 
$1$ 
Yes 
Bound type identifier 
$2$ 
Yes 
Bound name 
$3$ 
Yes 
Column name 
$4$ 
Yes/No 
Value 
Note: field 4 is required only if the bound type identifier is one of UP, LO, FX, UI or LI in which case it gives the value $k$ below. If the bound type identifier is FR, MI, PL or BV, field 4 is ignored and it is recommended to leave it blank.
The table below describes the acceptable bound type identifiers and how each determines the variables' bounds.
Bound Type Identifier 
$\mathit{l}$ 
$\mathit{u}$ 
Integer Variable? 
UP 
unchanged 
$k$ 
No 
LO 
$k$ 
unchanged 
No 
FX 
$k$ 
$k$ 
No 
FR 
$\infty $ 
$\infty $ 
No 
MI 
$\infty $ 
unchanged 
No 
PL 
unchanged 
$\infty $ 
No 
BV 
$0$ 
$1$ 
Yes 
UI 
unchanged 
$k$ 
Yes 
LI 
$k$ 
unchanged 
Yes 
If a bound name is defined in
${\mathbf{pnames}}\left[4\right]$ (see
Section 5) then the function will read in only the bound set of that name, otherwise the first set will be used.
3.1.9
QUADOBJ Section (optional)
The QUADOBJ section defines nonzero elements of the upper or lower triangle of the Hessian matrix
$H$.
Field 
Required 
Description 
$2$ 
Yes 
Column name (HColumn Index) 
$3$ 
Yes 
Column name (HRow Index) 
$4$ 
Yes 
Value 
$5$ 
No 
Column name (HRow Index) 
$6$ 
No 
Value 
Each data line in the QUADOBJ section defines one (or optionally two) nonzero elements
${H}_{ij}$ of the matrix
$H$. Each element
${H}_{ij}$ is given as a triplet of row index
$i$, column index
$j$ and a value. The column names (as defined in the COLUMNS section) are used to link the names of the variables and the indices
$i$ and
$j$. More precisely, the matrix
$H$ on output will have a nonzero element
where index
$j$ belongs to HColumn Index and index
$i$ to one of the HRow Indices such that
 ${\mathbf{crname}}\left[j1\right]=\text{Column name (HColumn Index)}$ and
 ${\mathbf{crname}}\left[i1\right]=\text{Column name (HRow Index)}$.
It is only necessary to define either the upper or lower triangle of the $H$ matrix; either will suffice. Any elements that have been defined in the upper triangle of the matrix will be moved to the lower triangle of the matrix, then any repeated nonzeros will be summed.
Note: it is much more efficient for
nag_opt_sparse_convex_qp_solve (e04nqc)
to have the
$H$ matrix defined by the first
ncolh column names. If the nonzeros of
$H$ are defined by any columns that are not in the first
ncolh of
n then
nag_opt_miqp_mps_read (e04mxc) will rearrange the matrices
$A$ and
$H$ so that they are.
3.2
Query Mode
nag_opt_miqp_mps_read (e04mxc) offers a ‘query mode’ to quickly give upper estimates on the sizes of user arrays. In this mode any expensive checks of the data and of the file format are skipped, providing a prompt count of the number of variables, constraints and matrix nonzeros. This might be useful in the common case where the size of the problem is not known in advance.
You may activate query mode by setting any of the following:
${\mathbf{maxn}}<1$,
${\mathbf{maxm}}<1$,
${\mathbf{maxnnz}}<1$,
${\mathbf{maxncolh}}<0$ or
${\mathbf{maxnnzh}}<0$. If no major formatting error is detected in the data file,
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_NOERROR is returned and the upper estimates are given as stated in
Table 1. Alternatively, the function switches to query mode while the file is being read if it is discovered that the provided space is insufficient (that is, if
${\mathbf{n}}>{\mathbf{maxn}}$,
${\mathbf{m}}>{\mathbf{maxm}}$,
${\mathbf{nnz}}>{\mathbf{maxnnz}}$,
${\mathbf{ncolh}}>{\mathbf{maxncolh}}$,
${\mathbf{nnzh}}>{\mathbf{maxnnzh}}$ or
${\mathbf{lintvar}}>{\mathbf{maxlintvar}}$). In this case
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX is returned.
The recommended practice is shown in
Section 10, where the function is invoked twice. The first call queries the array lengths required, after which the data arrays are allocated to be of these sizes. The second call reads the data using the sufficientlysized arrays.
4
References
IBM (1971) MPSX – Mathematical programming system Program Number 5734 XM4 IBM Trade Corporation, New York
5
Arguments
 1:
$\mathbf{fileid}$ – Nag_FileIDInput

On entry: the ID of the MPSX data file to be read as returned by a call to
nag_open_file (x04acc).
Constraint:
${\mathbf{fileid}}\ge 0$.
 2:
$\mathbf{maxn}$ – IntegerInput

On entry: an upper limit for the number of variables in the problem.
If
${\mathbf{maxn}}<1$,
nag_opt_miqp_mps_read (e04mxc) will start in query mode (see
Section 3.2).
 3:
$\mathbf{maxm}$ – IntegerInput

On entry: an upper limit for the number of general linear constraints (including the objective row) in the problem.
If
${\mathbf{maxm}}<1$,
nag_opt_miqp_mps_read (e04mxc) will start in query mode (see
Section 3.2).
 4:
$\mathbf{maxnnz}$ – IntegerInput

On entry: an upper limit for the number of nonzeros (including the objective row) in the problem.
If
${\mathbf{maxnnz}}<1$,
nag_opt_miqp_mps_read (e04mxc) will start in query mode (see
Section 3.2).
 5:
$\mathbf{maxncolh}$ – IntegerInput

On entry: an upper limit for the dimension of the matrix
$H$.
If
${\mathbf{maxncolh}}<0$,
nag_opt_miqp_mps_read (e04mxc) will start in query mode (see
Section 3.2).
 6:
$\mathbf{maxnnzh}$ – IntegerInput

On entry: an upper limit for the number of nonzeros of the matrix
$H$.
If
${\mathbf{maxnnzh}}<0$,
nag_opt_miqp_mps_read (e04mxc) will start in query mode (see
Section 3.2).
 7:
$\mathbf{maxlintvar}$ – IntegerInput

On entry: if
${\mathbf{maxlintvar}}\ge 0$, an upper limit for the number of integer variables.
If ${\mathbf{maxlintvar}}<0$, nag_opt_miqp_mps_read (e04mxc) will treat all integer variables in the file as continuous variables.
 8:
$\mathbf{mpslst}$ – IntegerInput

On entry: if ${\mathbf{mpslst}}\ne 0$, summary messages are sent to
stdout
as nag_opt_miqp_mps_read (e04mxc) reads through the data file. This can be useful for debugging the file. If ${\mathbf{mpslst}}=0$, then no summary is produced.
 9:
$\mathbf{n}$ – Integer *Output

On exit: if
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX, an upper estimate of the number of variables of the problem. Otherwise,
$n$, the actual number of variables in the problem.
 10:
$\mathbf{m}$ – Integer *Output

On exit: if
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX, an upper estimate of the number of general linear constraints in the problem (including the objective row). Otherwise
$m$, the actual number of general linear constraints of the problem.
 11:
$\mathbf{nnz}$ – Integer *Output

On exit: if
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX, an upper estimate of the number of nonzeros in the problem (including the objective row). Otherwise the actual number of nonzeros in the problem (including the objective row).
 12:
$\mathbf{ncolh}$ – Integer *Output

On exit: if
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX, an upper estimate of
the value of
ncolh required by
nag_opt_sparse_convex_qp_solve (e04nqc).
In this context
ncolh is the number of leading nonzero columns of the Hessian matrix
$H$. Otherwise, the actual dimension of the matrix
$H$.
 13:
$\mathbf{nnzh}$ – Integer *Output

On exit: if
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX, an upper estimate of the number of nonzeros of the matrix
$H$. Otherwise, the actual number of nonzeros of the matrix
$H$.
 14:
$\mathbf{lintvar}$ – Integer *Output

On exit: if on entry
${\mathbf{maxlintvar}}<0$, all integer variables are treated as continuous and
${\mathbf{lintvar}}=1$.
If
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX, an upper estimate of the number of integer variables of the problem. Otherwise, the actual number of integer variables of the problem.
 15:
$\mathbf{iobj}$ – Integer *Output

On exit: if
${\mathbf{iobj}}>0$, row
iobj of
$A$ is a free row containing the nonzero coefficients of the vector
$c$.
If ${\mathbf{iobj}}=0$, the coefficients of $c$ are assumed to be zero.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2)
iobj is not referenced and may be
NULL.
 16:
$\mathbf{a}\left[\mathit{dim}\right]$ – doubleOutput

Note: the dimension,
dim, of the array
a
must be at least
maxnnz when
${\mathbf{maxnnz}}>0$.
On exit: the nonzero elements of
$A$, ordered by increasing column index.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
a is not referenced and may be
NULL.
 17:
$\mathbf{irowa}\left[\mathit{dim}\right]$ – IntegerOutput

Note: the dimension,
dim, of the array
irowa
must be at least
maxnnz when
${\mathbf{maxnnz}}>0$.
On exit: the row indices of the nonzero elements stored in
a.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
irowa is not referenced and may be
NULL.
 18:
$\mathbf{iccola}\left[\mathit{dim}\right]$ – IntegerOutput

Note: the dimension,
dim, of the array
iccola
must be at least
${\mathbf{maxn}}+1$ when
${\mathbf{maxn}}>0$.
On exit: a set of pointers to the beginning of each column of
$A$. More precisely,
${\mathbf{iccola}}\left[\mathit{i}1\right]$ contains the index in
a of the start of the
$\mathit{i}$th column, for
$\mathit{i}=1,2,\dots ,{\mathbf{n}}$. Note that
${\mathbf{iccola}}\left[0\right]=1$ and
${\mathbf{iccola}}\left[{\mathbf{n}}\right]={\mathbf{nnz}}+1$.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
iccola is not referenced and may be
NULL.
 19:
$\mathbf{bl}\left[\mathit{dim}\right]$ – doubleOutput
 20:
$\mathbf{bu}\left[\mathit{dim}\right]$ – doubleOutput

Note: the dimension,
dim, of the arrays
bl and
bu
must be at least
${\mathbf{maxn}}+{\mathbf{maxm}}$ when
${\mathbf{maxn}}>0$ and
${\mathbf{maxm}}>0$.
On exit:
bl contains the vector
$l$ (the lower bounds) and
bu contains the vector
$u$ (the upper bounds), for all the variables and constraints in the following order. The first
n elements of each array contains the bounds on the variables
$x$ and the next
m elements contains the bounds for the linear objective term
${c}^{\mathrm{T}}x$ and for the general linear constraints
$Ax$ (if any). Note that an ‘infinite’ lower bound is indicated by
${\mathbf{bl}}\left[j1\right]=\text{1.0e+20}$ and an ‘infinite’ upper bound by
${\mathbf{bu}}\left[j1\right]=+\text{1.0e+20}$. In other words, any element of
$u$ greater than or equal to
${10}^{20}$ will be regarded as
$+\infty $ (and similarly any element of
$l$ less than or equal to
${10}^{20}$ will be regarded as
$\infty $). If this value is deemed to be ‘inappropriate’,
before calling
nag_opt_sparse_convex_qp_solve (e04nqc)
you are recommended to reset the value of its optional parameter
${\mathbf{Infinite\; Bound\; Size}}$ and make any necessary changes to
bl and/or
bu.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
bl and
bu are not referenced and may be
NULL.
 21:
$\mathbf{pnames}\left[5\right]\left[9\right]$ – char Input/Output

On entry: a set of names associated with the MPSX form of the problem.
 ${\mathbf{pnames}}\left[0\right]$
 Must either contain the name of the problem or be blank.
 ${\mathbf{pnames}}\left[1\right]$
 Must either be blank or contain the name of the objective row (in which case it overrides the OBJNAME section and the default choice of the first objective free row).
 ${\mathbf{pnames}}\left[2\right]$
 Must either contain the name of the RHS set to be used or be blank (in which case the first RHS set is used).
 ${\mathbf{pnames}}\left[3\right]$
 Must either contain the name of the RANGE set to be used or be blank (in which case the first RANGE set (if any) is used).
 ${\mathbf{pnames}}\left[4\right]$
 Must either contain the name of the BOUNDS set to be used or be blank (in which case the first BOUNDS set (if any) is used).
On exit: a set of names associated with the problem as defined in the MPSX data file as follows:
 ${\mathbf{pnames}}\left[0\right]$
 Contains the name of the problem (or blank if none).
 ${\mathbf{pnames}}\left[1\right]$
 Contains the name of the objective row (or blank if none).
 ${\mathbf{pnames}}\left[2\right]$
 Contains the name of the RHS set (or blank if none).
 ${\mathbf{pnames}}\left[3\right]$
 Contains the name of the RANGE set (or blank if none).
 ${\mathbf{pnames}}\left[4\right]$
 Contains the name of the BOUNDS set (or blank if none).
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
pnames is not referenced and may be
NULL.
 22:
$\mathbf{nname}$ – Integer *Output

On exit:
$n+m$, the total number of variables and constraints in the problem (including the objective row).
If
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX,
nname is not set. In the former case you may pass
NULL instead.
 23:
$\mathbf{crname}\left[\mathit{dim}\right]\left[9\right]$ – char Output

Note: the dimension,
dim, of the array
crname
must be at least
${\mathbf{maxn}}+{\mathbf{maxm}}$ when
${\mathbf{maxn}}>0$ and
${\mathbf{maxm}}>0$.
On exit: the MPS names of all the variables and constraints in the problem in the following order. The first
n elements contain the MPS names for the variables and the next
m elements contain the MPS names for the objective row and general linear constraints (if any). Note that the MPS name for the objective row is stored in
${\mathbf{crname}}\left[{\mathbf{n}}+{\mathbf{iobj}}1\right]$.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
crname is not referenced and may be
NULL.
 24:
$\mathbf{h}\left[\mathit{dim}\right]$ – doubleOutput

Note: the dimension,
dim, of the array
h
must be at least
maxnnzh when
${\mathbf{maxnnzh}}>0$.
On exit: the
nnzh nonzero elements of
$H$, arranged by increasing column index.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
h is not referenced and may be
NULL.
 25:
$\mathbf{irowh}\left[\mathit{dim}\right]$ – IntegerOutput

Note: the dimension,
dim, of the array
irowh
must be at least
maxnnzh when
${\mathbf{maxnnzh}}>0$.
On exit: the
nnzh row indices of the elements stored in
$H$.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
irowh is not referenced and may be
NULL.
 26:
$\mathbf{iccolh}\left[\mathit{dim}\right]$ – IntegerOutput

Note: the dimension,
dim, of the array
iccolh
must be at least
${\mathbf{maxncolh}}+1$ when
${\mathbf{maxncolh}}>0$.
On exit: a set of pointers to the beginning of each column of
$H$. More precisely,
${\mathbf{iccolh}}\left[\mathit{i}1\right]$ contains the index in
$H$ of the start of the
$\mathit{i}$th column, for
$\mathit{i}=1,2,\dots ,{\mathbf{ncolh}}$. Note that
${\mathbf{iccolh}}\left[0\right]=1$ and
${\mathbf{iccolh}}\left[{\mathbf{ncolh}}\right]={\mathbf{nnzh}}+1$.
If
nag_opt_miqp_mps_read (e04mxc) is run in query mode (see
Section 3.2),
iccolh is not referenced and may be
NULL.
 27:
$\mathbf{minmax}$ – Integer *Output

On exit:
minmax defines the direction of the optimization as read from the MPS file. By default the function assumes the objective function should be minimized and will return
${\mathbf{minmax}}=1$. If the function discovers in the OBJSENSE section that the objective function should be maximized it will return
${\mathbf{minmax}}=1$. If the function discovers that there is neither the linear objective term
$c$ (the objective row) nor the Hessian matrix
$H$, the problem is considered as a feasible point problem and
${\mathbf{minmax}}=0$ is returned.
If
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX,
minmax is not set. In the former case you may pass
NULL instead.
 28:
$\mathbf{intvar}\left[\mathit{dim}\right]$ – IntegerOutput

Note: the dimension,
dim, of the array
intvar
must be at least
maxlintvar, when
${\mathbf{maxlintvar}}>0$.
On exit: if
${\mathbf{maxlintvar}}>0$ on entry,
intvar contains pointers to the columns that are defined as integer variables. More precisely,
${\mathbf{intvar}}\left[\mathit{i}1\right]=k$, where
$k$ is the index of a column that is defined as an integer variable, for
$\mathit{i}=1,2,\dots ,{\mathbf{lintvar}}$.
If
${\mathbf{maxlintvar}}\le 0$ on entry, or
nag_opt_miqp_mps_read (e04mxc) was run in query mode (see
Section 3.2), or it returned with
${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_INT_MAX,
intvar is not set. Excepting the latter case you may pass
NULL as this argument instead.
 29:
$\mathbf{fail}$ – NagError *Input/Output

The NAG error argument (see
Section 3.7 in How to Use the NAG Library and its Documentation).
Note that if any of the relevant arguments are accidentally set to zero, or not set and assume zero values, then the function will have executed in query mode. In this case only the size of the problem is returned and other arguments are not set. See
Section 3.2.
6
Error Indicators and Warnings
 NE_ALLOC_FAIL

Dynamic memory allocation failed.
See
Section 2.3.1.2 in How to Use the NAG Library and its Documentation for further information.
 NE_BAD_PARAM

On entry, argument $\u2329\mathit{\text{value}}\u232a$ had an illegal value.
 NE_FILEID

On entry, ${\mathbf{fileid}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{fileid}}\ge 0$.
 NE_INT_MAX

At least one of
maxm,
maxn,
maxnnz,
maxnnzh,
maxncolh or
maxlintvar is too small.
Suggested values are returned in
m,
n,
nnz,
nnzh,
ncolh and
lintvar respectively.
 NE_INTERNAL_ERROR

An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact
NAG for assistance.
See
Section 2.7.6 in How to Use the NAG Library and its Documentation for further information.
 NE_MPS_BOUNDS

The supplied name, in ${\mathbf{pnames}}\left[4\right]$, of the BOUNDS set to be used was not found in the BOUNDS section.
Unknown bound type ‘$\u2329\mathit{\text{value}}\u232a$’ in BOUNDS section.
 NE_MPS_COLUMNS

Column ‘
$\u2329\mathit{\text{value}}\u232a$’ has been defined more than once in the COLUMNS section. Column definitions must be continuous. (See
Section 3.1.5).
Unknown column name ‘$\u2329\mathit{\text{value}}\u232a$’ in $\u2329\mathit{\text{value}}\u232a$ section.
All column names must be specified in the COLUMNS section.
 NE_MPS_ENDATA_NOT_FOUND

End of file found before ENDATA indicator line.
 NE_MPS_FORMAT

Warning: MPS file not strictly fixed format, although the problem was read anyway. The data may have been read incorrectly. You should set ${\mathbf{mpslst}}=1$ and repeat the call to nag_opt_miqp_mps_read (e04mxc) for more details.
 NE_MPS_ILLEGAL_DATA_LINE

An illegal line was detected in ‘$\u2329\mathit{\text{value}}\u232a$’ section.
This is neither a comment nor a valid data line.
 NE_MPS_ILLEGAL_NUMBER

Field
$\u2329\mathit{\text{value}}\u232a$ did not contain a number (see
Section 3).
 NE_MPS_INDICATOR

Incorrect ordering of indicator lines.
BOUNDS indicator line found before COLUMNS indicator line.
Incorrect ordering of indicator lines.
COLUMNS indicator line found before ROWS indicator line.
Incorrect ordering of indicator lines.
OBJNAME indicator line found after ROWS indicator line.
Incorrect ordering of indicator lines.
QUADOBJ indicator line found before BOUNDS indicator line.
Incorrect ordering of indicator lines.
QUADOBJ indicator line found before COLUMNS indicator line.
Incorrect ordering of indicator lines.
RANGES indicator line found before RHS indicator line.
Incorrect ordering of indicator lines.
RHS indicator line found before COLUMNS indicator line.
Indicator line ‘$\u2329\mathit{\text{value}}\u232a$’ has been found more than once in the MPS file.
No indicator line found in file. It may be an empty file.
Unknown indicator line ‘$\u2329\mathit{\text{value}}\u232a$’.
 NE_MPS_INVALID_INTORG_INTEND

Found ‘INTEND’ marker without previous marker being ‘INTORG’.
Found ‘INTORG’ but not ‘INTEND’ before the end of the COLUMNS section.
Found ‘INTORG’ marker within ‘INTORG’ to ‘INTEND’ range.
Illegal marker type ‘$\u2329\mathit{\text{value}}\u232a$’.
Should be either ‘INTORG’ or ‘INTEND’.
 NE_MPS_MANDATORY

At least one mandatory section not found in MPS file.
 NE_MPS_OBJNAME

The supplied name, in ${\mathbf{pnames}}\left[1\right]$ or in OBJNAME, of the objective row was not found among the free rows in the ROWS section.
 NE_MPS_PRINTABLE

Illegal column name.
Column names must consist of printable characters only.
Illegal row name.
Row names must consist of printable characters only.
 NE_MPS_RANGES

The supplied name, in ${\mathbf{pnames}}\left[3\right]$, of the RANGES set to be used was not found in the RANGES section.
 NE_MPS_REPEAT_COLUMN

More than one nonzero of
a has row name ‘
$\u2329\mathit{\text{value}}\u232a$’ and column name ‘
$\u2329\mathit{\text{value}}\u232a$’ in the COLUMNS section.
 NE_MPS_REPEAT_ROW

Row name ‘$\u2329\mathit{\text{value}}\u232a$’ has been defined more than once in the ROWS section.
 NE_MPS_RHS

The supplied name, in ${\mathbf{pnames}}\left[2\right]$, of the RHS set to be used was not found in the RHS section.
 NE_MPS_ROWS

Unknown inequality key ‘$\u2329\mathit{\text{value}}\u232a$’ in ROWS section.
Expected ‘N’, ‘G’, ‘L’ or ‘E’.
Unknown row name ‘$\u2329\mathit{\text{value}}\u232a$’ in $\u2329\mathit{\text{value}}\u232a$ section.
All row names must be specified in the ROWS section.
 NE_MPS_ROWS_OR_CONS

Empty ROWS section.
Neither the objective row nor the constraints were defined.
 NE_NO_LICENCE

Your licence key may have expired or may not have been installed correctly.
See
Section 2.7.5 in How to Use the NAG Library and its Documentation for further information.
7
Accuracy
Not applicable.
8
Parallelism and Performance
nag_opt_miqp_mps_read (e04mxc) makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the
x06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the
Users' Note for your implementation for any additional implementationspecific information.
None.
10
Example
This example solves the quadratic programming problem
where
The optimal solution (to five figures) is
Three bound constraints and two general linear constraints are active at the solution. Note that, although the Hessian matrix is only positive semidefinite, the point ${x}^{*}$ is unique.
The MPS representation of the problem is given in
Section 10.2.
Another example which shows how to use
nag_opt_miqp_mps_read (e04mxc) together with the NAG optimization modelling suite is associated with
nag_opt_handle_set_linconstr (e04rjc).
10.1
Program Text
Program Text (e04mxce.c)
10.2
Program Data
Program Options (e04mxce.opt)
10.3
Program Results
Program Results (e04mxce.r)