The LP format captures an optimization model in a way that is easier for humans to read than MPS format, and can often be more natural to produce. One limitation of the LP format is that it doesn't preserve several model properties. In particular, LP files do not preserve column order when read, and they typically don't preserve the exact numerical values of the coefficients (although this isn't inherent to the format).
Unlike MPS files, LP files do not rely on fixed field widths. Line breaks and whitespace characters are used to separate objects. Here is a simple example:
\ LP format example Maximize x + y + z Subject To c0: x + y = 1 c1: x + 5 y + 2 z <= 10 qc0: x + y + [ x ^ 2 - 2 x * y + 3 y ^ 2 ] <= 5 Bounds 0 <= x <= 5 z >= 2 Generals x y z End
The backslash symbol starts a comment; the remainder of that line is ignored.
Variable names play a major role in LP files. Each variable must have its
own unique name. A name should be no longer than 255 characters, and to
avoid confusing the LP parser, it can not begin with a number or
any of the characters
+, -, *, ^, <, >, =, (, ), [, ], ,, or :.
For similar reasons, a name should not contain any of the characters
+, -, *, ^, or :.
Also, variable names should not be equal (case insensitive) to any of
the LP file format keywords, e.g.,
st, bounds, min, max, binary, or end.
Names must be preceded and followed by whitespace.
The same rules apply to any other type of names in the LP format, e.g., constraint names or the objective name.
Note that whitespace characters are not optional in the Gurobi LP format. Thus,
for example, the text
x+y+z would be treated as a single
variable name, while
x + y + z would be treated as a three
LP files are structured as a list of sections, where each section captures a logical piece of the whole optimization model. Sections begin with particular keywords, and must generally come in a fixed order, although a few are allowed to be interchanged.
The first section in an LP file is the objective section. This section begins with one of the following six keywords: minimize, maximize, minimum, maximum, min, or max. Capitalization is ignored. This keyword may appear alone, or it may be immediately followed by multi-objectives, which indicates that the model contains multiple objective functions.
Let us consider single-objective models first, where this header is followed by a single linear or quadratic expression that captures the objective function.
The objective optionally begins with a label. A label consists of a name, followed by a colon character, following by a space. A space is allowed between the name and the colon, but not required.
The objective then continues with a list of linear terms, separated by
- operators. A term can contain a
coefficient and a variable (e.g.,
4.5 x), or just a variable
x). The objective can be spread over many lines, or it
may be listed on a single line. Line breaks can come between tokens,
but never within tokens.
The objective may optionally continue with a list of quadratic terms.
The quadratic portion of the objective expression begins with a
[ symbol and ends with a
] symbol, followed by
/ 2. These brackets should enclose one or more quadratic terms.
Either squared terms (e.g.,
2 x ^ 2) or product terms
3 x * y) are accepted. Coefficients on the quadratic
terms are optional.
For variables with piecewise-linear objective functions, the objective
section will include a
__pwl(x) term, where
x is the
name of the variable. The actual piecewise-linear expressions are
pulled from the later
The objective expression must always end with a line break.
An objective section might look like the following:
Minimize obj: 3.1 x + 4.5 y + 10 z + [ x ^ 2 + 2 x * y + 3 y ^ 2 ] / 2
In the multi-objective case, the header is followed by one or more
linear objective functions, where each starts with its own sub-header. The
sub-header gives the name of the objective, followed by a number of
fields that provide a Priority, Weight,
absolute tolerance (AbsTol) and relative tolerance
(RelTol) for that objective (see
ObjNRelTol for details on the meanings
of these fields).
The fields start with the field
name, followed by a
=, followed by the value. For
OBJ0: Priority=2 Weight=1 AbsTol=0 RelTol=0Please refer to the multi-objective section for additional details.
Each sub-header is followed by a linear expression that captures that objective.
A complete multi-objective section might look like the following:
Minimize multi-objectives OBJ0: Priority=2 Weight=1 AbsTol=0 RelTol=0 3.1 x + 4.5 y + 10 z OBJ1: Priority=1 Weight=1 AbsTol=0 RelTol=0 10 x + 0.1 y
The objective section is optional. The objective is set to 0 when it is not present.
The next section is the constraints section. It begins with one of the following headers, on its own line: subject to, such that, st, or s.t.. Capitalization is ignored.
The constraint section can have an arbitrary number of constraints.
Each constraint starts with an optional label (constraint name,
followed by a colon, followed by a space), continues with a linear
expression, followed by an optional quadratic expression (enclosed
in square brackets), and ends with a comparison operator, followed by a
numerical value, followed by a line break. Valid comparison
>. Note that LP format does not distinguish between strict and
non-strict inequalities, so for example
Note that the left-hand side of a constraint may not contain a constant term; the constant must appear on the right-hand side.
The following is a simple example of a valid linear constraint:
c0: 2.5 x + 2.3 y + 5.3 z <= 8.1The following is a valid quadratic constraint:
qc0: 3.1 x + 4.5 y + 10 z + [ x ^ 2 + 2 x * y + 3 y ^ 2 ] <= 10
The constraint section may also contain another constraint type: the
so-called indicator constraint. Indicator constraints start with an
optional label (constraint name, followed by a colon, followed by a
space), followed by a binary variable, a space, a
=, again a
space and a value, either
1. They continue with a
space, followed by
->, and again a space and finally a linear
constraint (without a label).
c0: b1 = 1 -> 2.5 x + 2.3 y + 5.3 z <= 8.1
This example constraint requires the given linear constraint to be
satisfied if the variable
b1 takes a value of
Every LP format file must have a constraints section.
Lazy Constraints Section
The next section is the lazy constraints section. It begins with the line
Lazy Constraints, optionally followed by a space and a laziness level
1-3 (if no laziness level is specified 1 is assumed), and continues with a
list of linear constraints in the exact same format as the linear
constraints in the constraints section. For example:
Lazy Constraints c0: 2.5 x + 2.3 y + 5.3 z <= 8.1 Lazy Constraints 2 c1: 1.5 x + 3.3 y + 4.3 z <= 8.1
Lazy constraints are linear constraints, and they are semantically equivalent to standard linear constraints. Depending on their laziness level they are enforced differently by the MIP solver. Please refer to the description of the Lazy attribute for details.
This section is optional.
User Cuts Section
The next section is the user cuts section. It begins with the line
User Cuts, on its own line, and is followed by a list of linear
constraints in the exact same format as the linear constraints in the
constraints section. For example:
User Cuts c0: 2.5 x + 2.3 y + 5.3 z <= 8.1
User cuts are linear constraints, and they are semantically equivalent to standard linear constraints. Please refer to the description of the Lazy attribute for details.
This section is optional.
The next section is the bounds section. It begins with the word
Bounds, on its own line, and is followed by a list of variable
bounds. Each line specifies the lower bound, the upper bound, or both
for a single variable. The keywords
can be used in the bounds section to specify infinite bounds. A bound
line can also indicate that a variable is
free, meaning that
it is unbounded in either direction.
Here are examples of valid bound lines:
0 <= x0 <= 1 x1 <= 1.2 x2 >= 3 x3 free x2 >= -Inf
It is not necessary to specify bounds for all variables; by default, each variable has a lower bound of 0 and an infinite upper bound. In fact, the entire bounds section is optional.
Variable Type Section
The next section is the variable types section. Variables can be designated as being either binary, general integer, or semi-continuous. In all cases, the designation is applied by first providing the appropriate header (on its own line), and then listing the variables that have the associated type. For example:
Binary x y zVariable type designations don't need to appear in any particular order (e.g., general integers can either precede or follow binaries). If a variable is included in multiple sections, the last one determines the variable type.
Valid keywords for variable type headers are: binary, binaries, bin, general, generals, gen, semi-continuous, semis, or semi.
The variable types section is optional. By default, variables are assumed to be continuous.
An LP file can contain a section that captures SOS constraints of type
1 or type 2. The SOS section begins with the
SOS header on
its own line (capitalization isn't important). An arbitrary number of
SOS constraints can follow. An SOS constraint starts with a name,
followed by a colon (unlike linear constraints, the name is not
optional here). Next comes the SOS type, which can be either
S2. The type is followed by a pair of colons.
Next come the members of the SOS set, along with their weights. Each member is captured using the variable name, followed by a colon, followed by the associated weight. Spaces can optionally be placed before and after the colon. An SOS constraint must end with a line break.
Here's an example of an SOS section containing two SOS constraints:
SOS sos1: S1 :: x1 : 1 x2 : 2 x3 : 3 sos2: S2 :: x4:8.5 x5:10.2 x6:18.3
The SOS section is optional.
An LP file can contain a section that captures piecewise-linear
objective functions. The PWL section begins with the
header on its own line (capitalization isn't important). Each
piecewise-linear objective function is associated with a model
variable. A PWL function starts with the corresponding variable name,
followed immediately by a colon (the name is not optional). Next come
the points that define the piecewise-linear function. These points
are represented as
(x, y) pairs, with parenthesis surrounding
the two values and a comma separating them. A PWL function must end
with a line break.
Here's an example of a PWLObj section containing two simple piecewise-linear functions:
PWLObj x1: (1, 1) (2, 2) (3, 4) x2: (1, 3) (3, 5) (100, 300)
The PWLObj section is optional.
General Constraint Section
An LP file may contain an optional section that captures general constraints. This section starts with one of the following keywords general constraints, general constraint, gencons, or g.c. (capitalization is ignored).
General constraints can be of two basic types: simple general
constraints - MIN, MAX, OR, AND, NORM,
ABS, or PWL, or function constraints -
POLY), power (
POW), exponential (
EXPA), logarithmic (
LOGA), logistic (
A simple general constraint starts with an optional label (constraint
name, followed by a colon), followed by a variable name (the so-called
resultant), then an equals sign
=. The line continues
with a general constraint type specifier (MIN, MAX,
OR, AND, NORM, or ABS), then a
(. All tokens
must be separated using spaces. Capitalization is ignored.
What follows depends on the general constraint type. MIN or MAX constraints expect a non-empty, comma-separated list of variables or values. OR and AND constraints expect a comma-separated list of binary variables. NORM expects a norm type (0, 1, 2, or INF), in parenthesis, followed by a comma-separated list of variables. ABS constraints expect only one variable name. Again, all tokens (including commas) must be separated using spaces.
All of these general constraints end with a
) and a line break.
Here are a few examples:
gc0: r1 = MAX ( x1 , x2 , x10 , 0.7 ) gencons1: r2 = MIN ( y0 , 10 , y1 , r1 ) and1: r = AND ( b1 , b2 ) or1: r = OR ( b3 , b4 ) norm2: r = NORM ( 2 ) ( x1 , y1, z1 ) GC14: xabs = ABS ( x )
Piecewise-linear constraints also start with an optional label (constraint
name, followed by a colon). The line continues with a variable name (the
so-called resultant) and an equal sign
=. Next comes the
keyword PWL that indicates that the constraint is of type
piecewise-linear. This is followed by a
(, and then by a variable
name (the so-called operand) followed by a
). The line
continues with a
: and then the list of piecewise-linear breakpoints
in parentheses (e.g., (x0, y0) (x1, y1)) with non-decreasing values on x.
Recall that spaces are required between tokens.
Here an example:
GC0: y = PWL ( x ) : (-1, 2) (0, 1) (0, 0) (0, 1) (1, 2)
There is one other type of simple constraint, the INDICATOR constraint. Those appear in the regular constraints section (described above), not in the general constraint section.
Function constraints also start with an optional label (constraint
name, followed by a colon). An optional list of attribute assignments
follows. These start with a
(, then a space-separate list of
Name=Value strings (no spaces before or after the
closed with a
). An example is shown below. Default values
are used if no attributes are specified.
The line continues with a variable name (the so-called resultant)
and an equal sign
=. Next comes a keyword that indicates the type
of function being defined (POLY, POW, EXP, EXPA, LOG, LOG_A, LOGISTIC, SIN, COS, or TAN). For a LOG, use LOG_A if it isn't a natural
log, where is the base. This is followed by a
(, and then by
the expression that defines the actual function. The line closes with a
). Recall that spaces are required between tokens.
Polynomials and powers are described in what is hopefully the natural
way, with exponents preceded by the
The following give examples of a few function constraints:
gc1: ( FuncPieceError=1e-05 FuncPieceRatio=0.5 ) z = SIN ( y ) GC2: ( FuncPieceLength=0.001 ) y = POLY ( 5 x ^ 3 + 2 x + 5 ) gc3: z = EXPA ( 3.5 ^ y ) gc4: z = LOG_10 ( y ) logytoz: z = LOG ( y )
For more information, consult the general constraint discussion.
An LP file may contain an optional section that captures scenario data. A model can have multiple scenarios, where each defines a set of changes to the original model (which we refer to as the base model).
This section starts with the Scenario keyword (capitalization is ignored), followed by a scenario name. Scenarios are described as a set of changes to the objective function, the right-hand sides of linear constraints, and the bounds of variables. Objective changes are stated first, followed by right-hand side changes, then bound changes. A scenario can be empty (i.e., identical to the base model).
Changes to the objective function start with one of the allowed
objective keywords (
Maximize, etc.; see
objective section above for additional information). Note that the
keyword needs to match the objective sense of the base model. This is
followed by a line for each changed objective coefficient that
contains the variable name and its modified value (separated by a
Changes to the right-hand sides of linear constraints start with one
of the allowed constraint section keywords (
Subject To, etc.;
see the constraints section above for additional information). This
is followed by a line for each changed right-hand side value that
contains the constraint name followed by a colon, then a space, the
constraint sense, a space, and the scenario right-hand side value.
Changes to variable bounds start with the
Bounds keyword. This
is followed by a line for each variable with changed scenario bounds;
the format of each such line is the same as in the bounds section above.
The following example shows three scenarios in LP format:
Scenario scenario0 Scenario scenario1 Maximize x1 0 x2 1 Subject To c1: <= 2 c2: >= 2 Bounds x3 <= 1.5 x1 free 0 <= x2 <= 0 x3 >= 0.5 Scenario scenario2 Bounds x3 = 3
For more information, consult the multiple scenario discussion.
The last line in an LP format file should be an