Constraints

A technical manual for constraints in InfiniteOpt. See the respective guide for more information.

Definition

Note that constraints are defined principally with JuMP.@constraint which originates from JuMP.jl. Below we show build methods for DomainRestrictedConstraints, but any JuMP.AbstractConstraint can be used.

InfiniteOpt.DomainRestrictionsType
DomainRestrictions{P <: GeneralVariableRef}

A DataType for storing interval domains that constrain particular infinite parameters to a subdomain relative to their full domain. This is used to define subdomains of DomainRestrictedConstraints. Note that the GeneralVariableRef must pertain to infinite parameters.

The constructor syntax is

DomainRestrictions(restrictions...)

where each argument of restrictions is one of the following forms:

  • pref => value
  • pref => [lb, ub]
  • pref => IntervalDomain(lb, ub)
  • prefs => value
  • prefs => [lb, ub]
  • prefs => IntervalDomain(lb, ub).

Note that pref and prefs must correspond to infinite parameters.

Fields

  • intervals::Dict{GeneralVariableRef, IntervalDomain}: A dictionary of interval bounds on infinite parameters.
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JuMP.build_constraintMethod
JuMP.build_constraint(_error::Function, func, set,
                      restrictions::DomainRestrictions{GeneralVariableRef}
                      )::DomainRestrictedConstraint

Extend JuMP.buid_constraint to handle including restrictions to its inherit infinite parameter domains in addition to the traditional func in set setup. This returns a DomainRestrictedConstraint that can then be added via JuMP.add_constraint. Errors if the restrictions are incompadible with infinite parameter domains.

Example

julia> restrictions = DomainRestrictions(t => 0)
Subdomain restrictions (1): t = 0

julia> con = build_constraint(error, y + 2, MOI.LessThan(0.0), restrictions);
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InfiniteOpt.DomainRestrictedConstraintType
DomainRestrictedConstraint{C <: JuMP.AbstractConstraint, 
                           P <: GeneralVariableRef
                           } <: JuMP.AbstractConstraint

A DataType for creating a constraint with enforced DomainRestrictions. For example this may pertain to a boundary condition.

Fields

  • constraint::C: The optimization constraint.
  • restrictions::DomainRestrictions{P}: The restrictions that determine the sub-domain of the constraint.
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JuMP.add_constraintMethod
JuMP.add_constraint(model::InfiniteModel, c::JuMP.AbstractConstraint,
                    [name::String = ""])::InfOptConstraintRef

Extend JuMP.add_constraint to add a constraint c to an infinite model model with name name. Returns an appropriate constraint reference whose type depends on what variables are used to define the constraint. Errors if any variables do not belong to model. This is primarily used as an internal method for the constraint macros.

Example

julia> @infinite_parameter(model, t in [0, 10]);

julia> @variable(model, g, Infinite(t));

julia> @variable(model, x);

julia> constr = build_constraint(error, g + x, MOI.EqualTo(42));

julia> cref = add_constraint(model, constr, "name")
name : g(t) + x = 42.0, ∀ t ∈ [0, 10]
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InfiniteOpt.ConstraintDataType
ConstraintData{C <: JuMP.AbstractConstraint} <: AbstractDataObject

A mutable DataType for storing constraints and their data.

Fields

  • constraint::C: The constraint.
  • object_nums::Vector{Int}: The object numbers of the parameter objects that the constraint depends on.
  • name::String: The name used for printing.
  • measure_indices::Vector{MeasureIndex}: Indices of dependent measures.
  • is_info_constraint::Bool: Is this is constraint based on variable info (e.g., lower bound)
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InfiniteOpt.InfOptConstraintRefType
InfOptConstraintRef

A DataType for constraints that are in InfiniteModels

Fields

  • model::InfiniteModel: Infinite model.
  • index::InfOptConstraintIndex: Index of the constraint in model.
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Queries

JuMP.owner_modelMethod
JuMP.owner_model(cref::InfOptConstraintRef)::InfiniteModel

Extend JuMP.owner_model to return the infinite model associated with cref.

Example

julia> model = owner_model(cref)
An InfiniteOpt Model
Minimization problem with:
Finite Parameters: 0
Infinite Parameters: 3
Variables: 3
Derivatives: 0
Measures: 0
Objective function type: GeneralVariableRef
`GenericAffExpr{Float64,GeneralVariableRef}`-in-`MathOptInterface.EqualTo{Float64}`: 1 constraint
Names registered in the model: g, t, h, x
Optimizer model backend information:
Model mode: AUTOMATIC
CachingOptimizer state: NO_OPTIMIZER
Solver name: No optimizer attached.
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JuMP.indexMethod
JuMP.index(cref::InfOptConstraintRef)::InfOptConstraintIndex

Extend JuMP.index to return the index of an InfiniteOpt constraint cref.

Example

julia> index(cref)
InfOptConstraintIndex(2)
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JuMP.constraint_objectMethod
JuMP.constraint_object(cref::InfOptConstraintRef)::JuMP.AbstractConstraint

Extend JuMP.constraint_object to return the constraint object associated with cref.

Example

julia> @infinite_parameter(model, t in [0, 10]);

julia> @variable(model, x <= 1);

julia> cref = UpperBoundRef(x);

julia> obj = constraint_object(cref)
ScalarConstraint{GeneralVariableRef,MathOptInterface.LessThan{Float64}}(x,
MathOptInterface.LessThan{Float64}(1.0))
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JuMP.nameMethod
JuMP.name(cref::InfOptConstraintRef)::String

Extend JuMP.name to return the name of an InfiniteOpt constraint.

Example

julia> name(cref)
"constr_name"
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JuMP.constraint_by_nameMethod
JuMP.constraint_by_name(model::InfiniteModel,
                        name::String)::Union{InfOptConstraintRef, Nothing}

Extend JuMP.constraint_by_name to return the constraint reference associated with name if one exists or returns nothing. Errors if more than one constraint uses the same name.

Example

julia> constraint_by_name(model, "constr_name")
constr_name : x + pt = 3.0
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JuMP.list_of_constraint_typesMethod
JuMP.list_of_constraint_types(model::InfiniteModel)::Vector{Tuple{DataType, DataType}}

Extend JuMP.list_of_constraint_types to return a list of tuples that contain all the used combinations of function types and set types in the model.

Example

julia> all_constraints(model)
3-element Array{Tuple{DataType,DataType},1}:
 (GeneralVariableRef, MathOptInterface.LessThan{Float64})
 (GeneralVariableRef, MathOptInterface.GreaterThan{Float64})
 (GeneralVariableRef, MathOptInterface.Integer)
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JuMP.num_constraintsMethod
JuMP.num_constraints(model::InfiniteModel, [function_type], [set_type])::Int

Extend JuMP.num_constraints to return the number of constraints with a partiuclar function type and set type.

Example

julia> num_constraints(model, FiniteVariableRef, MOI.LessThan)
1

julia> num_constraints(model, FiniteVariableRef)
3

julia> num_constraints(model, MOI.LessThan)
2

julia> num_constraints(model)
4
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JuMP.all_constraintsMethod
JuMP.all_constraints(model::InfiniteModel, [function_type], [set_type])::Vector{InfOptConstraintRef}

Extend JuMP.all_constraints to return a list of all the constraints with a particular function type and set type.

Example

julia> all_constraints(model, GeneralVariableRef, MOI.LessThan)
1-element Array{InfOptConstraintRef,1}:
 x ≤ 1.0

julia> all_constraints(model, GeneralVariableRef)
3-element Array{InfOptConstraintRef,1}:
 x ≥ 0.0
 x ≤ 3.0
 x integer

julia> all_constraints(model, MOI.GreaterThan)
3-element Array{InfOptConstraintRef,1}:
 x ≥ 0.0
 g(t) ≥ 0.0, ∀ t ∈ [0, 6]
 g(0.5) ≥ 0.0

julia> all_constraints(model)
5-element Array{InfOptConstraintRef,1}:
 x ≥ 0.0
 x ≤ 3.0
 x integer
 g(t) ≥ 0.0, ∀ t ∈ [0, 6]
 g(0.5) ≥ 0.0
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JuMP.is_validMethod
JuMP.is_valid(model::InfiniteModel, cref::InfOptConstraintRef)::Bool

Extend JuMP.is_valid to return Bool whether an InfiniteOpt constraint reference is valid.

Example

julia> is_valid(model, cref)
true
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InfiniteOpt.parameter_refsMethod
parameter_refs(cref::InfOptConstraintRef)::Tuple

Return the tuple of infinite parameter references that determine the infinite dependencies of cref.

Example

julia> parameter_refs(cref)
(t,)
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InfiniteOpt.domain_restrictionsFunction
domain_restrictions(cref::InfOptConstraintRef)::DomainRestrictions{GeneralVariableRef}

Return the DomainRestrictions object associated with the constraint cref.

Example

julia> domain_restrictions(cref)
Subdomain restrictions (1): t ∈ [0, 2]
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JuMP.normalized_rhsMethod
JuMP.normalized_rhs(cref::InfOptConstraintRef)::Float64

Return the right-hand side term of cref after JuMP has converted the constraint into its normalized form.

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JuMP.normalized_coefficientMethod
JuMP.normalized_coefficient(cref::InfOptConstraintRef,
                            variable::GeneralVariableRef)::Float64

Return the coefficient associated with variable in constraint after JuMP has normalized the constraint into its standard form.

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Modification

JuMP.set_nameMethod
JuMP.set_name(cref::InfOptConstraintRef, name::String)::Nothing

Extend JuMP.set_name to specify the name of a constraint cref.

Example

julia> set_name(cref, "new_name")

julia> name(cref)
"new_name"
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InfiniteOpt.set_domain_restrictionsFunction
set_domain_restrictions(cref::InfOptConstraintRef,
                     restrictions:DomainRestrictions{GeneralVariableRef};
                     [force::Bool = false])::Nothing

Specify a new DomainRestrictions object restrictions for the constraint cref. Errors if cref already has restrictions and force = false. Where possible it is recommended to use add_domain_restrictions instead.

Example

julia> set_domain_restrictions(cref, DomainRestrictions(t => [0, 2]))

julia> domain_restrictions(cref)
Subdomain restrictions (1): t ∈ [0, 2]
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InfiniteOpt.add_domain_restrictionsFunction
add_domain_restrictions(cref::InfOptConstraintRef,
                     new_restrictions::DomainRestrictions{GeneralVariableRef}
                     )::Nothing

Add additional domain restrictions to cref such that it is defined over the sub-domain based on pref from lower to upper.

julia> add_domain_restrictions(cref, DomainRestrictions(t => [0, 2]))

julia> domain_restrictions(cref)
Subdomain restrictions (1): t ∈ [0, 2]
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InfiniteOpt.delete_domain_restrictionsFunction
delete_domain_restrictions(cref::InfOptConstraintRef)::Nothing

Delete all the domain restrictions of the constraint cref. Note any restrictions that are needed for finite variables inside in cref will be unaffected.

Example

julia> @constraint(model, c1, y <= 42, DomainRestrictions(x => 0))
c1 : y(x) ≤ 42, ∀ x[1] = 0, x[2] = 0

julia> delete_domain_restrictions(c1)

julia> c1
c1 : y(x) ≤ 42, ∀ x[1] ∈ [-1, 1], x[2] ∈ [-1, 1]
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JuMP.set_normalized_rhsMethod
JuMP.set_normalized_rhs(cref::InfOptConstraintRef, value::Real)::Nothing

Set the right-hand side term of constraint to value. Note that prior to this step, JuMP will aggregate all constant terms onto the right-hand side of the constraint. For example, given a constraint 2x + 1 <= 2, set_normalized_rhs(con, 4) will create the constraint 2x <= 4, not 2x + 1 <= 4.

julia> @constraint(model, con, 2x + 1 <= 2)
con : 2 x ≤ 1.0

julia> set_normalized_rhs(con, 4)

julia> con
con : 2 x ≤ 4.0
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JuMP.add_to_function_constantMethod
JuMP.add_to_function_constant(cref::InfOptConstraintRef, value::Real)::Nothing

Add value to the function constant term. Note that for scalar constraints, JuMP will aggregate all constant terms onto the right-hand side of the constraint so instead of modifying the function, the set will be translated by -value. For example, given a constraint 2x <= 3, add_to_function_constant(c, 4) will modify it to 2x <= -1. ```

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JuMP.set_normalized_coefficientMethod
JuMP.set_normalized_coefficient(cref::InfOptConstraintRef,
                                variable::GeneralVariableRef,
                                value::Real)::Nothing

Set the coefficient of variable in the constraint constraint to value. Note that prior to this step, JuMP will aggregate multiple terms containing the same variable. For example, given a constraint 2x + 3x <= 2, set_normalized_coefficient(con, x, 4) will create the constraint 4x <= 2.

julia> con
con : 5 x ≤ 2.0

julia> set_normalized_coefficient(con, x, 4)

julia> con
con : 4 x ≤ 2.0
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JuMP.deleteMethod
JuMP.delete(model::InfiniteModel, cref::InfOptConstraintRef)::Nothing

Extend JuMP.delete to delete an InfiniteOpt constraint and all associated information. Errors if cref is invalid.

Example

julia> print(model)
Min measure(g(t)*t) + z
Subject to
 z ≥ 0.0
 g(t) + z ≥ 42.0, ∀ t ∈ [0, 6]

julia> delete(model, cref)

julia> print(model)
Min measure(g(t)*t) + z
Subject to
 z ≥ 0.0
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