nag_opt_miqp_mps_read (e04mx) 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.

Syntax

[n, m, nz, ncolh, nnzh, lintvar, iobj, a, irowa, iccola, bl, bu, pnames, nname, crname, h, irowh, iccolh, minmax, intvar, ifail] = e04mx(infile, maxn, maxm, maxnnz, maxncolh, maxnnzh, maxlintvar, mpslst, pnames)

[n, m, nz, ncolh, nnzh, lintvar, iobj, a, irowa, iccola, bl, bu, pnames, nname, crname, h, irowh, iccolh, minmax, intvar, ifail] = nag_opt_miqp_mps_read(infile, maxn, maxm, maxnnz, maxncolh, maxnnzh, maxlintvar, mpslst, pnames)

Description

nag_opt_miqp_mps_read (e04mx) 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

n

matrix

A

, the vectors

l

u

c

(stored in row iobj of

A

) and the

n

n

Hessian matrix

H

for use with nag_opt_qpconvex1_sparse_solve (e04nk) and nag_opt_qpconvex2_sparse_solve (e04nq). These functions are designed to solve problems of the form

\underset{x}{minimize} c^{T} x + \frac{1}{2} x^{T} H x subject to l \leq \{\begin{matrix} x \\ A x \end{matrix}\} \leq u .

MPS input format

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	user-supplied 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	$2 - 3$	$5 - 12$	$15 - 22$	$25 - 36$	$40 - 47$	$50 - 61$
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

1.2345678

123.45678e−2

and

12345678e−07

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 non-blank character outside the predefined six fields and columns 72–80 is considered to be a major error (

ifail = 16

; see Error Indicators and Warnings), unless it is part of a comment.

NAME Section (optional)

The NAME section is the only section where the data must be on the same line as the indicator. The ‘user-supplied name’ must be in field

3

but may be blank.

Field	Required	Description
$3$	No	Name of the problem

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.

OBJNAME Section (optional)

The data line in this section can be used to specify the name of a free row (see ROWS Section) 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

pnames (2)

(see Arguments).

Field	Required	Description
$2$	No	Row name to be used as the objective function

Field 2 must contain a valid row name.

ROWS Section

The data lines in this section specify unique row (constraint) names and their inequality types (i.e., unconstrained,

=

\geq

\leq

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

3

Inequality Key	Description	$l$	$u$
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^{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 OBJNAME Section (optional)) or

pnames (2)

(see Arguments). 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.

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

c

. Any elements of

A

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

j + 1

th column, for

j = 1, 2, \dots, n - 1

. Rows may appear in any order within the column.

Integer Markers

For backward compatibility nag_opt_miqp_mps_read (e04mx) 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

^{'}

MARKER

^{'}

. The marker type must be

^{'}

INTORG

^{'}

to start reading integer variables and

^{'}

INTEND

^{'}

to finish reading integer variables. This implies that a row cannot be named

^{'}

MARKER

^{'}

^{'}

INTORG

^{'}

^{'}

INTEND

^{'}

. Please note that both marker tag and marker type comprise of

8

characters as a

^{'}

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

^{'}

INTORG

^{'}

marker and end with an

^{'}

INTEND

^{'}

marker and there should not be another marker between them.

Field 2 is ignored by nag_opt_miqp_mps_read (e04mx). 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.

RHS Section

This section specifies the right-hand 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

pnames (3)

(see Arguments) then nag_opt_miqp_mps_read (e04mx) 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 (e04mx). 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.

RANGES Section (optional)

Ranges are used to modify the interpretation of constraints defined in the ROWS section (see ROWS Section) to the form

l \leq A x \leq u

, where both

l

and

u

are finite. The range of the constraint is

r = u - l

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 $r$	$l$	$u$
E	$+$	$b$	$b + r$
E	$-$	$b + r$	$b$
G	$+ / -$	$b$	$b + \|r\|$
L	$+ / -$	$b - \|r\|$	$b$
N	$+ / -$	$- \infty$	$+ \infty$

If a range name is defined in

pnames (4)

(see Arguments) then the function will read in only the range set of that name, otherwise the first set will be used.

BOUNDS Section (optional)

These lines specify limits on the values of the variables (the quantities

l

and

u

l \leq x \leq 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	$l$	$u$	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

pnames (5)

(see Arguments) then the function will read in only the bound set of that name, otherwise the first set will be used.

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_{i j}

of the matrix

H

. Each element

H_{i j}

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

H_{i j} = Value

where index

j

belongs to HColumn Index and index

i

to one of the HRow Indices such that

$crname (j) = Column name (HColumn Index)$ and
$crname (i) = Column name (HRow Index)$ .

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_qpconvex1_sparse_solve (e04nk) and nag_opt_qpconvex2_sparse_solve (e04nq) 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 (e04mx) will rearrange the matrices

A

and

H

so that they are.

Query Mode

nag_opt_miqp_mps_read (e04mx) 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:

maxn < 1

maxm < 1

maxnnz < 1

maxncolh < 0

maxnnzh < 0

. If no major formatting error is detected in the data file,

ifail = 0

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

n > maxn

m > maxm

nz > maxnnz

ncolh > maxncolh

nnzh > maxnnzh

lintvar > maxlintvar

). In this case

ifail = 2

is returned.

Argument Name	Upper Estimate for
n	maxn
m	maxm
nz	maxnnz
ncolh	maxncolh
nnzh	maxnnzh
lintvar	maxlintvar

Table 1

The recommended practice is shown in Example, 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 sufficiently-sized arrays.

References

IBM (1971) MPSX – Mathematical programming system Program Number 5734 XM4 IBM Trade Corporation, New York

Parameters

Compulsory Input Parameters

1: $infile$ – int64int32nag_int scalar

The ID of the MPSX data file to be read as returned by a call to nag_file_open (x04ac).

Constraint:

infile \geq 0

2: $maxn$ – int64int32nag_int scalar

An upper limit for the number of variables in the problem.

maxn < 1

, nag_opt_miqp_mps_read (e04mx) will start in query mode (see Query Mode).

3: $maxm$ – int64int32nag_int scalar

An upper limit for the number of general linear constraints (including the objective row) in the problem.

maxm < 1

, nag_opt_miqp_mps_read (e04mx) will start in query mode (see Query Mode).

4: $maxnnz$ – int64int32nag_int scalar

An upper limit for the number of nonzeros (including the objective row) in the problem.

maxnnz < 1

, nag_opt_miqp_mps_read (e04mx) will start in query mode (see Query Mode).

5: $maxncolh$ – int64int32nag_int scalar

An upper limit for the dimension of the matrix

H

maxncolh < 0

, nag_opt_miqp_mps_read (e04mx) will start in query mode (see Query Mode).

6: $maxnnzh$ – int64int32nag_int scalar

An upper limit for the number of nonzeros of the matrix

H

maxnnzh < 0

, nag_opt_miqp_mps_read (e04mx) will start in query mode (see Query Mode).

7: $maxlintvar$ – int64int32nag_int scalar

maxlintvar \geq 0

, an upper limit for the number of integer variables.

maxlintvar < 0

, nag_opt_miqp_mps_read (e04mx) will treat all integer variables in the file as continuous variables.

8: $mpslst$ – int64int32nag_int scalar

mpslst \neq 0

, summary messages are sent to the current advisory message unit (as defined by nag_file_set_unit_advisory (x04ab)) as nag_opt_miqp_mps_read (e04mx) reads through the data file. This can be useful for debugging the file. If

mpslst = 0

, then no summary is produced.

9: $pnames (5)$ – cell array of strings

A set of names associated with the MPSX form of the problem.

$pnames (1)$: Must either contain the name of the problem or be blank.
$pnames (2)$: Must either be blank or contain the name of the objective row (in which case it overrides OBJNAME section and the default choice of the first objective free row).
$pnames (3)$: Must either contain the name of the RHS set to be used or be blank (in which case the first RHS set is used).
$pnames (4)$: 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).
$pnames (5)$: 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).

Optional Input Parameters

None.

Output Parameters

1: $n$ – int64int32nag_int scalar

If nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or returned with

ifail = 2

, an upper estimate of the number of variables of the problem. Otherwise,

n

, the actual number of variables in the problem.

2: $m$ – int64int32nag_int scalar

If nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or returned with

ifail = 2

, 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 constaints of the problem.

3: $nz$ – int64int32nag_int scalar

If nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or returned with

ifail = 2

, 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).

4: $ncolh$ – int64int32nag_int scalar

If nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or returned with

ifail = 2

, an upper estimate of the value of ncolh required by nag_opt_qpconvex1_sparse_solve (e04nk) and nag_opt_qpconvex2_sparse_solve (e04nq). In this context ncolh is the number of leading nonzero columns of the Hessian matrix

H

. Otherwise, the actual dimension of the matrix

H

5: $nnzh$ – int64int32nag_int scalar

If nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or returned with

ifail = 2

, an upper estimate of the number of nonzeros of the matrix

H

. Otherwise, the actual number of nonzeros of the matrix

H

6: $lintvar$ – int64int32nag_int scalar

If on entry

maxlintvar < 0

, all integer variables are treated as continuous and

lintvar = - 1

If nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or returned with

ifail = 2

, an upper estimate of the number of integer variables of the problem. Otherwise, the actual number of integer variables of the problem.

7: $iobj$ – int64int32nag_int scalar

iobj > 0

, row iobj of

A

is a free row containing the nonzero coefficients of the vector

c

iobj = 0

, the coefficients of

c

are assumed to be zero.

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode) iobj is not referenced.

8: $a (maxnnz)$ – double array

The nonzero elements of

A

, ordered by increasing column index.

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), a is not referenced.

9: $irowa (maxnnz)$ – int64int32nag_int array

The row indices of the nonzero elements stored in a.

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), irowa is not referenced.

10: $iccola (maxn + 1)$ – int64int32nag_int array

A set of pointers to the beginning of each column of

A

. More precisely,

iccola (i)

contains the index in a of the start of the

i

th column, for

i = 1, 2, \dots, n

. Note that

iccola (1) = 1

and

iccola (n + 1) = nz + 1

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), iccola is not referenced.

11: $bl (maxn + maxm)$ – double array

12: $bu (maxn + maxm)$ – double array

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^{T} x

and for the general linear constraints

A x

(if any). Note that an ‘infinite’ lower bound is indicated by

bl (j) = - 1.0e+20

and an ‘infinite’ upper bound by

bu (j) = + 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_qpconvex1_sparse_solve (e04nk) or nag_opt_qpconvex2_sparse_solve (e04nq) you are recommended to reset the value of its optional parameter nag_opt_qpconvex1_sparse_solve (e04nk) and nag_opt_qpconvex2_sparse_solve (e04nq) and make any necessary changes to bl and/or bu.

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), bl and bu are not referenced.

13: $pnames (5)$ – cell array of strings

A set of names associated with the problem as defined in the MPSX data file as follows:

$pnames (1)$: Contains the name of the problem (or blank if none).
$pnames (2)$: Contains the name of the objective row (or blank if none).
$pnames (3)$: Contains the name of the RHS set (or blank if none).
$pnames (4)$: Contains the name of the RANGE set (or blank if none).
$pnames (5)$: Contains the name of the BOUNDS set (or blank if none).

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), pnames is not referenced.

14: $nname$ – int64int32nag_int scalar

n + m

, the total number of variables and constraints in the problem (including the objective row).

If nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or returned with

ifail = 2

, nname is not set.

15: $crname (maxn + maxm)$ – cell array of strings

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

crname (n + iobj)

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), crname is not referenced.

16: $h (\max (0, maxnnzh))$ – double array

The nnzh nonzero elements of

H

, arranged by increasing column index.

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), h is not referenced.

17: $irowh (\max (0, maxnnzh))$ – int64int32nag_int array

The nnzh row indices of the elements stored in

H

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), irowh is not referenced.

18: $iccolh (maxncolh + 1)$ – int64int32nag_int array

A set of pointers to the beginning of each column of

H

. More precisely,

iccolh (i)

contains the index in

H

of the start of the

i

th column, for

i = 1, 2, \dots, ncolh

. Note that

iccolh (1) = 1

and

iccolh (ncolh + 1) = nnzh + 1

If nag_opt_miqp_mps_read (e04mx) is run in query mode (see Query Mode), iccolh is not referenced.

19: $minmax$ – int64int32nag_int scalar

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

minmax = - 1

. If the function discovers in the OBJSENSE section that the objective function should be maximized it will return

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

minmax = 0

is returned.

If nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or returned with

ifail = 2

, minmax is not set.

20: $intvar (\max (0, maxlintvar))$ – int64int32nag_int array

maxlintvar > 0

on entry, intvar contains pointers to the columns that are defined as integer variables. More precisely,

intvar (i) = k

, where

k

is the index of a column that is defined as an integer variable, for

i = 1, 2, \dots, lintvar

maxlintvar \leq 0

on entry, or nag_opt_miqp_mps_read (e04mx) was run in query mode (see Query Mode), or it returned with

ifail = 2

, intvar is not set.

21: $ifail$ – int64int32nag_int scalar

ifail = 0

unless the function detects an error (see Error Indicators and Warnings).

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 Query Mode.

Error Indicators and Warnings

Errors or warnings detected by the function:

Cases prefixed with W are classified as warnings and do not generate an error of type NAG:error_n. See nag_issue_warnings.

W $ifail = 1$: Warning: MPS file not strictly fixed format, although the problem was read anyway. The data may have been read incorrectly. You should set $mpslst = 1$ and repeat the call to nag_opt_miqp_mps_read (e04mx) for more details.

$ifail = 2$: At least one of maxm, maxn, maxnnz, maxnnzh, maxncolh or maxlintvar is too small.

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

$ifail = 3$: Incorrect ordering of indicator lines.
OBJNAME indicator line found after ROWS indicator line.

$ifail = 4$: Incorrect ordering of indicator lines.
COLUMNS indicator line found before ROWS indicator line.

$ifail = 5$: Incorrect ordering of indicator lines.
RHS indicator line found before COLUMNS indicator line.

$ifail = 6$: Incorrect ordering of indicator lines.
RANGES indicator line found before RHS indicator line.

$ifail = 7$: Incorrect ordering of indicator lines.
BOUNDS indicator line found before COLUMNS indicator line.

$ifail = 8$: Incorrect ordering of indicator lines.
QUADOBJ indicator line found before BOUNDS indicator line.

$ifail = 9$: Incorrect ordering of indicator lines.
QUADOBJ indicator line found before COLUMNS indicator line.

$ifail = 10$: Unknown indicator line ‘ $_$ ’.

$ifail = 12$: Indicator line ‘ $_$ ’ has been found more than once in the MPS file.

$ifail = 13$: End of file found before ENDATA indicator line.

$ifail = 14$: No indicator line found in file. It may be an empty file.

$ifail = 15$: At least one mandatory section not found in MPS file.

$ifail = 16$: An illegal line was detected in ‘ $_$ ’ section.
This is neither a comment nor a valid data line.

$ifail = 17$: Unknown inequality key ‘ $_$ ’ in ROWS section.
Expected ‘N’, ‘G’, ‘L’ or ‘E’.

$ifail = 18$: Empty ROWS section.
Neither the objective row nor the constraints were defined.

$ifail = 19$: The supplied name, in $pnames (2)$ or in OBJNAME, of the objective row was not found among the free rows in the ROWS section.

$ifail = 20$: The supplied name, in $pnames (5)$ , of the BOUNDS set to be used was not found in the BOUNDS section.

$ifail = 21$: The supplied name, in $pnames (3)$ , of the RHS set to be used was not found in the RHS section.

$ifail = 22$: The supplied name, in $pnames (4)$ , of the RANGES set to be used was not found in the RANGES section.

$ifail = 23$: Illegal row name.
Row names must consist of printable characters only.

$ifail = 24$: Illegal column name.
Column names must consist of printable characters only.

$ifail = 25$: Row name ‘ $_$ ’ has been defined more than once in the ROWS section.

$ifail = 26$: Column ‘ $_$ ’ has been defined more than once in the COLUMNS section. Column definitions must be continuous. (See COLUMNS Section).

$ifail = 27$: Found ‘INTORG’ marker within ‘INTORG’ to ‘INTEND’ range.

$ifail = 28$: Found ‘INTEND’ marker without previous marker being ‘INTORG’.

$ifail = 29$: Found ‘INTORG’ but not ‘INTEND’ before the end of the COLUMNS section.

$ifail = 30$: Illegal marker type ‘ $_$ ’.
Should be either ‘INTORG’ or ‘INTEND’.

$ifail = 31$: Unknown row name ‘ $_$ ’ in $_$ section.
All row names must be specified in the ROWS section.

$ifail = 32$: Unknown column name ‘ $_$ ’ in $_$ section.
All column names must be specified in the COLUMNS section.

$ifail = 33$: Unknown bound type ‘ $_$ ’ in BOUNDS section.

$ifail = 34$: More than one nonzero of a has row name ‘ $_$ ’ and column name ‘ $_$ ’ in the COLUMNS section.

$ifail = 35$: Field $_$ did not contain a number (see Description).

$ifail = 36$: Constraint: $infile \geq 0$ .

$ifail = - 99$: An unexpected error has been triggered by this routine. Please contact NAG.

$ifail = - 399$: Your licence key may have expired or may not have been installed correctly.

$ifail = - 999$: Dynamic memory allocation failed.

Accuracy

Not applicable.

Further Comments

None.

Example

This example solves the quadratic programming problem

minimize c^{T} x + \frac{1}{2} x^{T} H x subject to \begin{matrix} l & \leq A x & \leq u, \\ - 2 & \leq x & \leq 2, \end{matrix}

where

c = (\begin{matrix} - 4.0 \\ - 1.0 \\ - 1.0 \\ - 1.0 \\ - 1.0 \\ - 1.0 \\ - 1.0 \\ - 0.1 \\ - 0.3 \end{matrix}), H = (\begin{matrix} 2 & 1 & 1 & 1 & 1 & 0 & 0 & 0 & 0 \\ 1 & 2 & 1 & 1 & 1 & 0 & 0 & 0 & 0 \\ 1 & 1 & 2 & 1 & 1 & 0 & 0 & 0 & 0 \\ 1 & 1 & 1 & 2 & 1 & 0 & 0 & 0 & 0 \\ 1 & 1 & 1 & 1 & 2 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \end{matrix}),

A = (\begin{matrix} 1.0 & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 & 4.0 \\ 1.0 & 2.0 & 3.0 & 4.0 & - 2.0 & 1.0 & 1.0 & 1.0 & 1.0 \\ 1.0 & - 1.0 & 1.0 & - 1.0 & 1.0 & 1.0 & 1.0 & 1.0 & 1.0 \end{matrix}),

l = (\begin{matrix} - 2.0 \\ - 2.0 \\ - 2.0 \end{matrix}) and u = (\begin{matrix} 1.5 \\ 1.5 \\ 4.0 \end{matrix}) .

The optimal solution (to five figures) is

x^{*} = {(2.0, - 0.23333, - 0.26667, - 0.3, - 0.1, 2.0, 2.0, - 1.7777, - 0.45555)}^{T} .

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.

Open in the MATLAB editor: e04mx_example

e04mx.opt

NAME          E04MX.EX
ROWS
 L  ..ROW1..
 L  ..ROW2..
 L  ..ROW3..
 N  ..COST..
COLUMNS
    ...X1...  ..ROW1..      1.0        ..ROW2..         1.0
    ...X1...  ..ROW3..      1.0        ..COST..        -4.0
    ...X2...  ..ROW1..      1.0        ..ROW2..         2.0
    ...X2...  ..ROW3..     -1.0        ..COST..        -1.0
    ...X3...  ..ROW1..      1.0        ..ROW2..         3.0
    ...X3...  ..ROW3..      1.0        ..COST..        -1.0
    ...X4...  ..ROW1..      1.0        ..ROW2..         4.0
    ...X4...  ..ROW3..     -1.0        ..COST..        -1.0
    ...X5...  ..ROW1..      1.0        ..ROW2..        -2.0
    ...X5...  ..ROW3..      1.0        ..COST..        -1.0
    ...X6...  ..ROW1..      1.0        ..ROW2..         1.0
    ...X6...  ..ROW3..      1.0        ..COST..        -1.0
    ...X7...  ..ROW1..      1.0        ..ROW2..         1.0
    ...X7...  ..ROW3..      1.0        ..COST..        -1.0
    ...X8...  ..ROW1..      1.0        ..ROW2..         1.0
    ...X8...  ..ROW3..      1.0        ..COST..        -0.1
    ...X9...  ..ROW1..      4.0        ..ROW2..         1.0
    ...X9...  ..ROW3..      1.0        ..COST..        -0.3
RHS
    RHS1      ..ROW1..      1.5
    RHS1      ..ROW2..      1.5
    RHS1      ..ROW3..      4.0
    RHS1      ..COST..      1000.0
RANGES
    RANGE1    ..ROW1..      3.5
    RANGE1    ..ROW2..      3.5
    RANGE1    ..ROW3..      6.0
BOUNDS
 LO BOUND     ...X1...     -2.0
 LO BOUND     ...X2...     -2.0
 LO BOUND     ...X3...     -2.0
 LO BOUND     ...X4...     -2.0
 LO BOUND     ...X5...     -2.0
 LO BOUND     ...X6...     -2.0
 LO BOUND     ...X7...     -2.0
 LO BOUND     ...X8...     -2.0
 LO BOUND     ...X9...     -2.0
 UP BOUND     ...X1...      2.0
 UP BOUND     ...X2...      2.0
 UP BOUND     ...X3...      2.0
 UP BOUND     ...X4...      2.0
 UP BOUND     ...X5...      2.0
 UP BOUND     ...X6...      2.0
 UP BOUND     ...X7...      2.0
 UP BOUND     ...X8...      2.0
 UP BOUND     ...X9...      2.0
QUADOBJ
    ...X1...  ...X1...  2.00000000E0   ...X2...  1.00000000E0
    ...X1...  ...X3...  1.00000000E0   ...X4...  1.00000000E0
    ...X1...  ...X5...  1.00000000E0
    ...X2...  ...X2...  2.00000000E0   ...X3...  1.00000000E0
    ...X2...  ...X4...  1.00000000E0   ...X5...  1.00000000E0
    ...X3...  ...X3...  2.00000000E0   ...X4...  1.00000000E0
    ...X3...  ...X5...  1.00000000E0
    ...X4...  ...X4...  2.00000000E0   ...X5...  1.00000000E0
    ...X5...  ...X5...  2.00000000E0
ENDATA

function e04mx_example


fprintf('e04mx example results\n\n');

% Open the data file for reading to get max sizes for problem
nin     = int64(7);
mode    = int64(0);
[ifail] = x04ac(nin, 'e04mx.opt', mode);

% Call e04mx in query mode
n       = int64(0);
m       = int64(0);
nz      = int64(0);
ncolh   = int64(0);
nnzh    = int64(0);
lintvar = int64(-1);
mpslst  = int64(0);
pnames  = {'        ', '        ', '        ', '        ', '        '};
[n, m, nz, ncolh, nnzh, lintvar, iobj, a, irowa, iccola, bl, bu, pnames, ...
  nname, crname, h, irowh, iccolh, minmax, intvar, ifail] = ...
  e04mx(...
        nin, n, m, nz, ncolh, nnzh, lintvar, mpslst, pnames);

% Close the data file
[ifail] = x04ad(nin);

% Re-open the data file for reading the problem
[ifail] = x04ac(nin, 'e04mx.opt', mode);

% Call e04mx to read the problem after setting max sizes
maxm     = m;
maxn     = n;
maxnnz   = nz;
maxnnzh  = nnzh;
maxncolh = ncolh;
[n, m, nz, ncolh, nnzh, lintvar, iobj, a, irowa, iccola, bl, bu, pnames, ...
  nname, crname, h, irowh, iccolh, minmax, intvar, ifail] = ...
  e04mx(...
        nin, n, m, nz, ncolh, nnzh, lintvar, mpslst, pnames);

% Close the data file
[ifail] = x04ad(nin);

% Data has been read, set up and run the solver

% Initialise workspace
[cw, iw, rw, ifail] = e04np;

% Turn off printing and listing
[cw, iw, rw, ifail] = e04ns('NoList', cw, iw, rw);
[cw, iw, rw, ifail] = e04ns('Print Level = 0', cw, iw, rw);

% We have no explicit objective vector so set LENC = 0; the
% objective vector is stored in row IOBJ of ACOL.
lenc   = int64(0);
objadd = 0;
start  = 'c';

c      = zeros(lenc, 1);
helast = zeros(n+m, 1, 'int64');
hs     = zeros(n+m, 1, 'int64');
x      = zeros(n+m, 1);
for i=1:n+m
  x(i) = min(max(0, bl(i)),bu(i));
end
ns     = int64(0);

% Store the non zeros of H, iccolh and irowh in user for use by qphx
user = {h, iccolh, irowh};

% Call e04nq to solve the problem
[hs, x, pi, rc, ns, ninf, sinf, obj, user, cw, iw, rw, ifail] = ...
  e04nq(...
        start, @qphx, m, n, lenc, ncolh, iobj, objadd, pnames{1}, a, irowa, ...
        iccola, bl, bu, c, crname, helast, hs, x, ns, cw, iw, rw, 'user', user);
fprintf('Number of variables : %9d\n',n);
fprintf('Number of contraints: %9d\n',3);
fprintf('Minimum value       : %9.4f\n\n',obj);
fprintf('Variable values at minimum:\n');
fprintf('    %9.4f %9.4f %9.4f\n',x(1:n));
fprintf('Linear contrained values:\n');
fprintf('    %9.4f %9.4f %9.4f\n',x(n+1:n+3));



function [hx, user] = qphx(ncolh, x, nstate, user)
  hx = zeros(ncolh, 1);

  h      = user{1};
  iccolh = user{2};
  irowh  = user{3};

  for icol = 1:ncolh
    start = iccolh(icol);
    endd  = iccolh(icol+1)-1;

    for idx = start:endd
      irow     = irowh(idx);
      hx(irow) = hx(irow) + x(icol)*h(idx);
      if irow ~= icol
        hx (icol) = hx(icol) + x(irow)*h(idx);
      end
    end
  end

e04mx example results

Number of variables :         9
Number of contraints:         3
Minimum value       :   -8.0678

Variable values at minimum:
       2.0000   -0.2333   -0.2667
      -0.3000   -0.1000    2.0000
       2.0000   -1.7778   -0.4556
Linear contrained values:
       1.5000    1.5000    3.9333

PDF version (NAG web site, 64-bit version, 64-bit version)

Chapter Contents

Chapter Introduction

NAG Toolbox