# Bridges

## AbstractBridge API

`MathOptInterface.Bridges.AbstractBridge`

— Type`abstract type AbstractBridge end`

An abstract type representing a bridged constraint or variable in a `MathOptInterface.Bridges.AbstractBridgeOptimizer`

.

All bridges must implement:

`added_constrained_variable_types`

`added_constraint_types`

`MOI.get(::AbstractBridge, ::MOI.NumberOfVariables)`

`MOI.get(::AbstractBridge, ::MOI.ListOfVariableIndices)`

`MOI.get(::AbstractBridge, ::MOI.NumberOfConstraints)`

`MOI.get(::AbstractBridge, ::MOI.ListOfConstraintIndices)`

Subtypes of `AbstractBridge`

may have additional requirements. Consult their docstrings for details.

In addition, all subtypes may optionally implement the following constraint attributes with the bridge in place of the constraint index:

`MathOptInterface.Bridges.added_constrained_variable_types`

— Function```
added_constrained_variable_types(
BT::Type{<:AbstractBridge},
)::Vector{Tuple{Type}}
```

Return a list of the types of constrained variables that bridges of concrete type `BT`

add.

**Implementation notes**

- This method depends only on the type of the bridge, not the runtime value.

**Example**

```
julia> MOI.Bridges.added_constrained_variable_types(
MOI.Bridges.Variable.NonposToNonnegBridge{Float64},
)
1-element Vector{Tuple{Type}}:
(MathOptInterface.Nonnegatives,)
```

`MathOptInterface.Bridges.added_constraint_types`

— Function```
added_constraint_types(
BT::Type{<:AbstractBridge},
)::Vector{Tuple{Type,Type}}
```

Return a list of the types of constraints that bridges of concrete type `BT`

add.

**Implementation notes**

- This method depends only on the type of the bridge, not the runtime value.

**Example**

```
julia> MOI.Bridges.added_constraint_types(
MOI.Bridges.Constraint.ZeroOneBridge{Float64},
)
2-element Vector{Tuple{Type, Type}}:
(MathOptInterface.VariableIndex, MathOptInterface.Interval{Float64})
(MathOptInterface.VariableIndex, MathOptInterface.Integer)
```

`MathOptInterface.get`

— Method`MOI.get(b::AbstractBridge, ::MOI.NumberOfVariables)::Int64`

Return the number of variables created by the bridge `b`

in the model.

See also `MOI.NumberOfConstraints`

.

**Implementation notes**

- There is a default fallback, so you need only implement this if the bridge adds new variables.

`MathOptInterface.get`

— Method`MOI.get(b::AbstractBridge, ::MOI.ListOfVariableIndices)`

Return the list of variables created by the bridge `b`

.

See also `MOI.ListOfVariableIndices`

.

**Implementation notes**

- There is a default fallback, so you need only implement this if the bridge adds new variables.

`MathOptInterface.get`

— Method`MOI.get(b::AbstractBridge, ::MOI.NumberOfConstraints{F,S})::Int64 where {F,S}`

Return the number of constraints of the type `F`

-in-`S`

created by the bridge `b`

.

See also `MOI.NumberOfConstraints`

.

**Implementation notes**

- There is a default fallback, so you need only implement this for the constraint types returned by
`added_constraint_types`

.

`MathOptInterface.get`

— Method`MOI.get(b::AbstractBridge, ::MOI.ListOfConstraintIndices{F,S}) where {F,S}`

Return a `Vector{ConstraintIndex{F,S}}`

with indices of all constraints of type `F`

-in-`S`

created by the bride `b`

.

See also `MOI.ListOfConstraintIndices`

.

**Implementation notes**

- There is a default fallback, so you need only implement this for the constraint types returned by
`added_constraint_types`

.

`MathOptInterface.Bridges.needs_final_touch`

— Function`needs_final_touch(bridge::AbstractBridge)::Bool`

Return whether `final_touch`

is implemented by `bridge`

.

`MathOptInterface.Bridges.final_touch`

— Function`final_touch(bridge::AbstractBridge, model::MOI.ModelLike)::Nothing`

A function that is called immediately prior to `MOI.optimize!`

to allow bridges to modify their reformulations with repsect to other variables and constraints in `model`

.

For example, if the correctness of `bridge`

depends on the bounds of a variable or the fact that variables are integer, then the bridge can implement `final_touch`

to check assumptions immediately before a call to `MOI.optimize!`

.

If you implement this method, you must also implement `needs_final_touch`

.

## Constraint bridge API

`MathOptInterface.Bridges.Constraint.AbstractBridge`

— Type`abstract type AbstractBridge <: MOI.Bridges.AbstractType`

Subtype of `MOI.Bridges.AbstractBridge`

for constraint bridges.

In addition to the required implementation described in `MOI.Bridges.AbstractBridge`

, subtypes of `AbstractBridge`

must additionally implement:

`MathOptInterface.supports_constraint`

— Method```
MOI.supports_constraint(
BT::Type{<:AbstractBridge},
F::Type{<:MOI.AbstractFunction},
S::Type{<:MOI.AbstractSet},
)::Bool
```

Return a `Bool`

indicating whether the bridges of type `BT`

support bridging `F`

-in-`S`

constraints.

**Implementation notes**

- This method depends only on the type of the inputs, not the runtime values.
- There is a default fallback, so you need only implement this method for constraint types that the bridge implements.

`MathOptInterface.Bridges.Constraint.concrete_bridge_type`

— Function```
concrete_bridge_type(
BT::Type{<:AbstractBridge},
F::Type{<:MOI.AbstractFunction},
S::Type{<:MOI.AbstractSet}
)::Type
```

Return the concrete type of the bridge supporting `F`

-in-`S`

constraints.

This function can only be called if `MOI.supports_constraint(BT, F, S)`

is `true`

.

**Example**

The `SplitIntervalBridge`

bridges a `MOI.VariableIndex`

-in-`MOI.Interval`

constraint into a `MOI.VariableIndex`

-in-`MOI.GreaterThan`

and a `MOI.VariableIndex`

-in-`MOI.LessThan`

constraint.

```
julia> MOI.Bridges.Constraint.concrete_bridge_type(
MOI.Bridges.Constraint.SplitIntervalBridge{Float64},
MOI.VariableIndex,
MOI.Interval{Float64},
)
MathOptInterface.Bridges.Constraint.SplitIntervalBridge{Float64, MathOptInterface.VariableIndex, MathOptInterface.Interval{Float64}, MathOptInterface.GreaterThan{Float64}, MathOptInterface.LessThan{Float64}}
```

`MathOptInterface.Bridges.Constraint.bridge_constraint`

— Function```
bridge_constraint(
BT::Type{<:AbstractBridge},
model::MOI.ModelLike,
func::AbstractFunction,
set::MOI.AbstractSet,
)::BT
```

Bridge the constraint `func`

-in-`set`

using bridge `BT`

to `model`

and returns a bridge object of type `BT`

.

**Implementation notes**

- The bridge type
`BT`

should be a concrete type, that is, all the type parameters of the bridge must be set.

`MathOptInterface.Bridges.Constraint.AbstractFunctionConversionBridge`

— Type`abstract type AbstractFunctionConversionBridge{F,S} <: AbstractBridge end`

Abstract type to support writing bridges in which the function changes but the set does not.

By convention, the transformed function is stored in the `.constraint`

field.

`MathOptInterface.Bridges.Constraint.SingleBridgeOptimizer`

— Type`SingleBridgeOptimizer{BT<:AbstractBridge}(model::MOI.ModelLike)`

Return `AbstractBridgeOptimizer`

that always bridges any objective function supported by the bridge `BT`

.

This is in contrast with the `MathOptInterface.Bridges.LazyBridgeOptimizer`

, which only bridges the objective function if it is supported by the bridge `BT`

and unsupported by `model`

.

**Example**

```
julia> struct MyNewBridge{T} <: MOI.Bridges.Constraint.AbstractBridge end
julia> bridge = MOI.Bridges.Constraint.SingleBridgeOptimizer{MyNewBridge{Float64}}(
MOI.Utilities.Model{Float64}(),
)
MOIB.Constraint.SingleBridgeOptimizer{MyNewBridge{Float64}, MOIU.Model{Float64}}
with 0 constraint bridges
with inner model MOIU.Model{Float64}
```

**Implementation notes**

All bridges should simplify the creation of `SingleBridgeOptimizer`

s by defining a constant that wraps the bridge in a `SingleBridgeOptimizer`

.

```
julia> const MyNewBridgeModel{T,OT<:MOI.ModelLike} =
MOI.Bridges.Constraint.SingleBridgeOptimizer{MyNewBridge{T},OT};
```

This enables users to create bridged models as follows:

```
julia> MyNewBridgeModel{Float64}(MOI.Utilities.Model{Float64}())
MOIB.Constraint.SingleBridgeOptimizer{MyNewBridge{Float64}, MOIU.Model{Float64}}
with 0 constraint bridges
with inner model MOIU.Model{Float64}
```

`MathOptInterface.Bridges.Constraint.add_all_bridges`

— Function`add_all_bridges(bridged_model, ::Type{T}) where {T}`

Add all bridges defined in the `Bridges.Constraint`

submodule to `bridged_model`

. The coefficient type used is `T`

.

`MathOptInterface.Bridges.Constraint.FlipSignBridge`

— Type`FlipSignBridge{T,S1,S2,F,G}`

An abstract type that simplifies the creation of other bridges.

`MathOptInterface.Bridges.Constraint.AbstractToIntervalBridge`

— Type`AbstractToIntervalBridge{T<:AbstractFloat,S,F}`

An abstract type that simplifies the creation of other bridges.

`T`

must be a `AbstractFloat`

type because otherwise `typemin`

and `typemax`

would either be not implemented (e.g. `BigInt`

), or would not give infinite value (e.g. `Int`

). For this reason, this bridge is only added to `MOI.Bridges.full_bridge_optimizer`

when `T`

is a subtype of `AbstractFloat`

.

`MathOptInterface.Bridges.Constraint.SetMapBridge`

— Type`abstract type SetMapBridge{T,S2,S1,F,G} <: AbstractBridge end`

Consider two type of sets, `S1`

and `S2`

, and a linear mapping `A`

such that the image of a set of type `S1`

under `A`

is a set of type `S2`

.

A `SetMapBridge{T,S2,S1,F,G}`

is a bridge that maps `G`

-in-`S2`

constraints into `F`

-in-`S1`

by mapping the function through `A`

.

The linear map `A`

is described by;

Implementing a method for these two functions is sufficient to bridge constraints. However, in order for the getters and setters of attributes such as dual solutions and starting values to work as well, a method for the following functions must be implemented:

`MathOptInterface.Bridges.inverse_map_set`

`MathOptInterface.Bridges.inverse_map_function`

`MathOptInterface.Bridges.adjoint_map_function`

`MathOptInterface.Bridges.inverse_adjoint_map_function`

See the docstrings of each function to see which feature would be missing if it was not implemented for a given bridge.

## Objective bridge API

`MathOptInterface.Bridges.Objective.AbstractBridge`

— Type`abstract type AbstractBridge <: MOI.Bridges.AbstractBridge end`

Subtype of `MOI.Bridges.AbstractBridge`

for objective bridges.

In addition to the required implementation described in `MOI.Bridges.AbstractBridge`

, subtypes of `AbstractBridge`

must additionally implement:

`MathOptInterface.Bridges.Objective.supports_objective_function`

— Function```
supports_objective_function(
BT::Type{<:MOI.Bridges.Objective.AbstractBridge},
F::Type{<:MOI.AbstractScalarFunction},
)::Bool
```

Return a `Bool`

indicating whether the bridges of type `BT`

support bridging objective functions of type `F`

.

**Implementation notes**

- This method depends only on the type of the inputs, not the runtime values.
- There is a default fallback, so you need only implement this method For objective functions that the bridge implements.

`MathOptInterface.Bridges.set_objective_function_type`

— Function```
set_objective_function_type(
BT::Type{<:Objective.AbstractBridge},
)::Type{<:MOI.AbstractScalarFunction}
```

Return the type of objective function that bridges of concrete type `BT`

set.

**Implementation notes**

- This method depends only on the type of the bridge, not the runtime value.

**Example**

```
julia> MOI.Bridges.set_objective_function_type(
MOI.Bridges.Objective.FunctionizeBridge{Float64},
)
MathOptInterface.ScalarAffineFunction{Float64}
```

`MathOptInterface.Bridges.Objective.concrete_bridge_type`

— Function```
concrete_bridge_type(
BT::Type{<:MOI.Bridges.Objective.AbstractBridge},
F::Type{<:MOI.AbstractScalarFunction},
)::Type
```

Return the concrete type of the bridge supporting objective functions of type `F`

.

This function can only be called if `MOI.supports_objective_function(BT, F)`

is `true`

.

`MathOptInterface.Bridges.Objective.bridge_objective`

— Function```
bridge_objective(
BT::Type{<:MOI.Bridges.Objective.AbstractBridge},
model::MOI.ModelLike,
func::MOI.AbstractScalarFunction,
)::BT
```

Bridge the objective function `func`

using bridge `BT`

to `model`

and returns a bridge object of type `BT`

.

**Implementation notes**

- The bridge type
`BT`

must be a concrete type, that is, all the type parameters of the bridge must be set.

`MathOptInterface.Bridges.Objective.SingleBridgeOptimizer`

— Type`SingleBridgeOptimizer{BT<:AbstractBridge}(model::MOI.ModelLike)`

Return `AbstractBridgeOptimizer`

that always bridges any objective function supported by the bridge `BT`

.

This is in contrast with the `MathOptInterface.Bridges.LazyBridgeOptimizer`

, which only bridges the objective function if it is supported by the bridge `BT`

and unsupported by `model`

.

**Example**

```
julia> struct MyNewBridge{T} <: MOI.Bridges.Objective.AbstractBridge end
julia> bridge = MOI.Bridges.Objective.SingleBridgeOptimizer{MyNewBridge{Float64}}(
MOI.Utilities.Model{Float64}(),
)
MOIB.Objective.SingleBridgeOptimizer{MyNewBridge{Float64}, MOIU.Model{Float64}}
with 0 objective bridges
with inner model MOIU.Model{Float64}
```

**Implementation notes**

All bridges should simplify the creation of `SingleBridgeOptimizer`

s by defining a constant that wraps the bridge in a `SingleBridgeOptimizer`

.

```
julia> const MyNewBridgeModel{T,OT<:MOI.ModelLike} =
MOI.Bridges.Objective.SingleBridgeOptimizer{MyNewBridge{T},OT};
```

This enables users to create bridged models as follows:

```
julia> MyNewBridgeModel{Float64}(MOI.Utilities.Model{Float64}())
MOIB.Objective.SingleBridgeOptimizer{MyNewBridge{Float64}, MOIU.Model{Float64}}
with 0 objective bridges
with inner model MOIU.Model{Float64}
```

`MathOptInterface.Bridges.Objective.add_all_bridges`

— Function`add_all_bridges(model, ::Type{T}) where {T}`

Add all bridges defined in the `Bridges.Objective`

submodule to `model`

.

The coefficient type used is `T`

.

## Variable bridge API

`MathOptInterface.Bridges.Variable.AbstractBridge`

— Type`abstract type AbstractBridge <: MOI.Bridges.AbstractBridge end`

Subtype of `MOI.Bridges.AbstractBridge`

for variable bridges.

In addition to the required implementation described in `MOI.Bridges.AbstractBridge`

, subtypes of `AbstractBridge`

must additionally implement:

`MathOptInterface.Bridges.Variable.supports_constrained_variable`

— Function```
supports_constrained_variable(
BT::Type{<:AbstractBridge},
S::Type{<:MOI.AbstractSet},
)::Bool
```

Return a `Bool`

indicating whether the bridges of type `BT`

support bridging constrained variables in `S`

. That is, it returns `true`

if the bridge of type `BT`

converts constrained variables of type `S`

into a form supported by the solver.

**Implementation notes**

- This method depends only on the type of the bridge and set, not the runtime values.
- There is a default fallback, so you need only implement this method for sets that the bridge implements.

**Example**

```
julia> MOI.Bridges.Variable.supports_constrained_variable(
MOI.Bridges.Variable.NonposToNonnegBridge{Float64},
MOI.Nonpositives,
)
true
julia> MOI.Bridges.Variable.supports_constrained_variable(
MOI.Bridges.Variable.NonposToNonnegBridge{Float64},
MOI.Nonnegatives,
)
false
```

`MathOptInterface.Bridges.Variable.concrete_bridge_type`

— Function```
concrete_bridge_type(
BT::Type{<:AbstractBridge},
S::Type{<:MOI.AbstractSet},
)::Type
```

Return the concrete type of the bridge supporting variables in `S`

constraints.

This function can only be called if `MOI.supports_constrained_variable(BT, S)`

is `true`

.

**Examples**

As a variable in `MathOptInterface.GreaterThan`

is bridged into variables in `MathOptInterface.Nonnegatives`

by the `VectorizeBridge`

:

```
julia> MOI.Bridges.Variable.concrete_bridge_type(
MOI.Bridges.Variable.VectorizeBridge{Float64},
MOI.GreaterThan{Float64},
)
MathOptInterface.Bridges.Variable.VectorizeBridge{Float64, MathOptInterface.Nonnegatives}
```

`MathOptInterface.Bridges.Variable.bridge_constrained_variable`

— Function```
bridge_constrained_variable(
BT::Type{<:AbstractBridge},
model::MOI.ModelLike,
set::MOI.AbstractSet,
)::BT
```

Bridge the constrained variable in `set`

using bridge `BT`

to `model`

and returns a bridge object of type `BT`

.

**Implementation notes**

- The bridge type
`BT`

must be a concrete type, that is, all the type parameters of the bridge must be set.

`MathOptInterface.Bridges.Variable.SingleBridgeOptimizer`

— Type`SingleBridgeOptimizer{BT<:AbstractBridge}(model::MOI.ModelLike)`

Return `MOI.Bridges.AbstractBridgeOptimizer`

that always bridges any variables constrained on creation supported by the bridge `BT`

.

This is in contrast with the `MOI.Bridges.LazyBridgeOptimizer`

, which only bridges the variables constrained on creation if they are supported by the bridge `BT`

and unsupported by `model`

.

Two `SingleBridgeOptimizer`

s cannot be used together as both of them assume that the underlying model only returns variable indices with nonnegative values. Use `MOI.Bridges.LazyBridgeOptimizer`

instead.

**Example**

```
julia> struct MyNewBridge{T} <: MOI.Bridges.Variable.AbstractBridge end
julia> bridge = MOI.Bridges.Variable.SingleBridgeOptimizer{MyNewBridge{Float64}}(
MOI.Utilities.Model{Float64}(),
)
MOIB.Variable.SingleBridgeOptimizer{MyNewBridge{Float64}, MOIU.Model{Float64}}
with 0 variable bridges
with inner model MOIU.Model{Float64}
```

**Implementation notes**

All bridges should simplify the creation of `SingleBridgeOptimizer`

s by defining a constant that wraps the bridge in a `SingleBridgeOptimizer`

.

```
julia> const MyNewBridgeModel{T,OT<:MOI.ModelLike} =
MOI.Bridges.Variable.SingleBridgeOptimizer{MyNewBridge{T},OT};
```

This enables users to create bridged models as follows:

```
julia> MyNewBridgeModel{Float64}(MOI.Utilities.Model{Float64}())
MOIB.Variable.SingleBridgeOptimizer{MyNewBridge{Float64}, MOIU.Model{Float64}}
with 0 variable bridges
with inner model MOIU.Model{Float64}
```

`MathOptInterface.Bridges.Variable.add_all_bridges`

— Function`add_all_bridges(model, ::Type{T}) where {T}`

Add all bridges defined in the `Bridges.Variable`

submodule to `model`

.

The coefficient type used is `T`

.

`MathOptInterface.Bridges.Variable.FlipSignBridge`

— Type`abstract type FlipSignBridge{T,S1,S2} <: SetMapBridge{T,S2,S1} end`

An abstract type that simplifies the creation of other bridges.

`MathOptInterface.Bridges.Variable.SetMapBridge`

— Type`abstract type SetMapBridge{T,S1,S2} <: AbstractBridge end`

Consider two type of sets, `S1`

and `S2`

, and a linear mapping `A`

such that the image of a set of type `S1`

under `A`

is a set of type `S2`

.

A `SetMapBridge{T,S1,S2}`

is a bridge that substitutes constrained variables in `S2`

into the image through `A`

of constrained variables in `S1`

.

The linear map `A`

is described by:

Implementing a method for these two functions is sufficient to bridge constrained variables. However, in order for the getters and setters of attributes such as dual solutions and starting values to work as well, a method for the following functions must be implemented:

`MathOptInterface.Bridges.inverse_map_set`

`MathOptInterface.Bridges.inverse_map_function`

`MathOptInterface.Bridges.adjoint_map_function`

`MathOptInterface.Bridges.inverse_adjoint_map_function`

.

See the docstrings of each function to see which feature would be missing if it was not implemented for a given bridge.

`MathOptInterface.Bridges.Variable.unbridged_map`

— Function```
unbridged_map(
bridge::MOI.Bridges.Variable.AbstractBridge,
vi::MOI.VariableIndex,
)
```

For a bridged variable in a scalar set, return a tuple of pairs mapping the variables created by the bridge to an affine expression in terms of the bridged variable `vi`

.

```
unbridged_map(
bridge::MOI.Bridges.Variable.AbstractBridge,
vis::Vector{MOI.VariableIndex},
)
```

For a bridged variable in a vector set, return a tuple of pairs mapping the variables created by the bridge to an affine expression in terms of the bridged variable `vis`

. If this method is not implemented, it falls back to calling the following method for every variable of `vis`

.

```
unbridged_map(
bridge::MOI.Bridges.Variable.AbstractBridge,
vi::MOI.VariableIndex,
i::MOI.Bridges.IndexInVector,
)
```

For a bridged variable in a vector set, return a tuple of pairs mapping the variables created by the bridge to an affine expression in terms of the bridged variable `vi`

corresponding to the `i`

th variable of the vector.

If there is no way to recover the expression in terms of the bridged variable(s) `vi(s)`

, return `nothing`

. See `ZerosBridge`

for an example of bridge returning `nothing`

.

## AbstractBridgeOptimizer API

`MathOptInterface.Bridges.AbstractBridgeOptimizer`

— Type`abstract type AbstractBridgeOptimizer <: MOI.AbstractOptimizer end`

An abstract type that implements generic functions for bridges.

**Implementation notes**

By convention, the inner optimizer should be stored in a `model`

field. If not, the optimizer must implement `MOI.optimize!`

.

`MathOptInterface.Bridges.bridged_variable_function`

— Function```
bridged_variable_function(
b::AbstractBridgeOptimizer,
vi::MOI.VariableIndex,
)
```

Return a `MOI.AbstractScalarFunction`

of variables of `b.model`

that equals `vi`

. That is, if the variable `vi`

is bridged, it returns its expression in terms of the variables of `b.model`

. Otherwise, it returns `vi`

.

`MathOptInterface.Bridges.unbridged_variable_function`

— Function```
unbridged_variable_function(
b::AbstractBridgeOptimizer,
vi::MOI.VariableIndex,
)
```

Return a `MOI.AbstractScalarFunction`

of variables of `b`

that equals `vi`

. That is, if the variable `vi`

is an internal variable of `b.model`

created by a bridge but not visible to the user, it returns its expression in terms of the variables of bridged variables. Otherwise, it returns `vi`

.

`MathOptInterface.Bridges.bridged_function`

— Function`bridged_function(b::AbstractBridgeOptimizer, value)::typeof(value)`

Substitute any bridged `MOI.VariableIndex`

in `value`

by an equivalent expression in terms of variables of `b.model`

.

`MathOptInterface.Bridges.supports_constraint_bridges`

— Function`supports_constraint_bridges(b::AbstractBridgeOptimizer)::Bool`

Return a `Bool`

indicating if `b`

supports `MOI.Bridges.Constraint.AbstractBridge`

.

`MathOptInterface.Bridges.recursive_model`

— Function`recursive_model(b::AbstractBridgeOptimizer)`

If a variable, constraint, or objective is bridged, return the context of the inner variables. For most optimizers, this should be `b.model`

.

## LazyBridgeOptimizer API

`MathOptInterface.Bridges.LazyBridgeOptimizer`

— Type`LazyBridgeOptimizer(model::MOI.ModelLike)`

The `LazyBridgeOptimizer`

is a bridge optimizer that supports multiple bridges, and only bridges things which are not supported by the internal model.

Internally, the `LazyBridgeOptimizer`

solves a shortest hyper-path problem to determine which bridges to use.

In general, you should use `full_bridge_optimizer`

instead of this constructor because `full_bridge_optimizer`

automatically adds a large number of supported bridges.

See also: `add_bridge`

, `remove_bridge`

, `has_bridge`

and `full_bridge_optimizer`

.

**Example**

```
julia> model = MOI.Bridges.LazyBridgeOptimizer(MOI.Utilities.Model{Float64}())
MOIB.LazyBridgeOptimizer{MOIU.Model{Float64}}
with 0 variable bridges
with 0 constraint bridges
with 0 objective bridges
with inner model MOIU.Model{Float64}
julia> MOI.Bridges.add_bridge(model, MOI.Bridges.Variable.FreeBridge{Float64})
julia> MOI.Bridges.has_bridge(model, MOI.Bridges.Variable.FreeBridge{Float64})
true
```

`MathOptInterface.Bridges.full_bridge_optimizer`

— Function`full_bridge_optimizer(model::MOI.ModelLike, ::Type{T}) where {T}`

Returns a `LazyBridgeOptimizer`

bridging `model`

for every bridge defined in this package (see below for the few exceptions) and for the coefficient type `T`

, as well as the bridges in the list returned by the `ListOfNonstandardBridges`

attribute.

**Example**

```
julia> model = MOI.Utilities.Model{Float64}();
julia> bridged_model = MOI.Bridges.full_bridge_optimizer(model, Float64);
```

**Exceptions**

The following bridges are not added by `full_bridge_optimizer`

, except if they are in the list returned by the `ListOfNonstandardBridges`

attribute:

`Constraint.SOCtoNonConvexQuadBridge`

`Constraint.RSOCtoNonConvexQuadBridge`

](@ref)`Constraint.SOCtoPSDBridge`

- If
`T`

is not a subtype of`AbstractFloat`

, subtypes of`Constraint.AbstractToIntervalBridge`

See the docstring of the each bridge for the reason they are not added.

`MathOptInterface.Bridges.ListOfNonstandardBridges`

— Type`ListOfNonstandardBridges{T}() <: MOI.AbstractOptimizerAttribute`

Any optimizer can be wrapped in a `LazyBridgeOptimizer`

using `full_bridge_optimizer`

. However, by default `LazyBridgeOptimizer`

uses a limited set of bridges that are:

- implemented in
`MOI.Bridges`

- generally applicable for all optimizers.

For some optimizers however, it is useful to add additional bridges, such as those that are implemented in external packages (e.g., within the solver package itself) or only apply in certain circumstances (e.g., `Constraint.SOCtoNonConvexQuadBridge`

).

Such optimizers should implement the `ListOfNonstandardBridges`

attribute to return a vector of bridge types that are added by `full_bridge_optimizer`

in addition to the list of default bridges.

Note that optimizers implementing `ListOfNonstandardBridges`

may require package-specific functions or sets to be used if the non-standard bridges are not added. Therefore, you are recommended to use `model = MOI.instantiate(Package.Optimizer; with_bridge_type = T)`

instead of `model = MOI.instantiate(Package.Optimizer)`

. See `MathOptInterface.instantiate`

.

**Examples**

**An optimizer using a non-default bridge in MOI.Bridges**

Solvers supporting `MOI.ScalarQuadraticFunction`

can support `MOI.SecondOrderCone`

and `MOI.RotatedSecondOrderCone`

by defining:

```
function MOI.get(::MyQuadraticOptimizer, ::ListOfNonstandardBridges{Float64})
return Type[
MOI.Bridges.Constraint.SOCtoNonConvexQuadBridge{Float64},
MOI.Bridges.Constraint.RSOCtoNonConvexQuadBridge{Float64},
]
end
```

**An optimizer defining an internal bridge**

Suppose an optimizer can exploit specific structure of a constraint, e.g., it can exploit the structure of the matrix `A`

in the linear system of equations `A * x = b`

.

The optimizer can define the function:

```
struct MatrixAffineFunction{T} <: MOI.AbstractVectorFunction
A::SomeStructuredMatrixType{T}
b::Vector{T}
end
```

and then a bridge

```
struct MatrixAffineFunctionBridge{T} <: MOI.Constraint.AbstractBridge
# ...
end
# ...
```

from `VectorAffineFunction{T}`

to the `MatrixAffineFunction`

. Finally, it defines:

```
function MOI.get(::Optimizer{T}, ::ListOfNonstandardBridges{T}) where {T}
return Type[MatrixAffineFunctionBridge{T}]
end
```

`MathOptInterface.Bridges.add_bridge`

— Function`add_bridge(b::LazyBridgeOptimizer, BT::Type{<:AbstractBridge})`

Enable the use of the bridges of type `BT`

by `b`

.

`MathOptInterface.Bridges.remove_bridge`

— Function`remove_bridge(b::LazyBridgeOptimizer, BT::Type{<:AbstractBridge})`

Disable the use of the bridges of type `BT`

by `b`

.

`MathOptInterface.Bridges.has_bridge`

— Function`has_bridge(b::LazyBridgeOptimizer, BT::Type{<:AbstractBridge})`

Return a `Bool`

indicating whether the bridges of type `BT`

are used by `b`

.

`MathOptInterface.Bridges.print_active_bridges`

— Function`print_active_bridges([io::IO=stdout,] b::MOI.Bridges.LazyBridgeOptimizer)`

Print the set of bridges that are active in the model `b`

.

`MathOptInterface.Bridges.print_graph`

— Function`print_graph([io::IO = stdout,] b::LazyBridgeOptimizer)`

Print the hyper-graph containing all variable, constraint, and objective types that could be obtained by bridging the variables, constraints, and objectives that are present in the model by all the bridges added to `b`

.

Each node in the hyper-graph corresponds to a variable, constraint, or objective type.

- Variable nodes are indicated by
`[ ]`

- Constraint nodes are indicated by
`( )`

- Objective nodes are indicated by
`| |`

The number inside each pair of brackets is an index of the node in the hyper-graph.

Note that this hyper-graph is the full list of possible transformations. When the bridged model is created, we select the shortest hyper-path(s) from this graph, so many nodes may be un-used.

To see which nodes are used, call `print_active_bridges`

.

For more information, see Legat, B., Dowson, O., Garcia, J., and Lubin, M. (2020). "MathOptInterface: a data structure for mathematical optimization problems." URL: https://arxiv.org/abs/2002.03447

`MathOptInterface.Bridges.debug_supports_constraint`

— Function```
debug_supports_constraint(
b::LazyBridgeOptimizer,
F::Type{<:MOI.AbstractFunction},
S::Type{<:MOI.AbstractSet};
io::IO = Base.stdout,
)
```

Prints to `io`

explanations for the value of `MOI.supports_constraint`

with the same arguments.

`MathOptInterface.Bridges.debug_supports`

— Function```
debug_supports(
b::LazyBridgeOptimizer,
::MOI.ObjectiveFunction{F};
io::IO = Base.stdout,
) where F
```

Prints to `io`

explanations for the value of `MOI.supports`

with the same arguments.

## SetMap API

`MathOptInterface.Bridges.map_set`

— Function`map_set(::Type{BT}, set) where {BT}`

Return the image of `set`

through the linear map `A`

defined in `Variable.SetMapBridge`

and `Constraint.SetMapBridge`

. This is used for bridging the constraint and setting the `MathOptInterface.ConstraintSet`

.

`MathOptInterface.Bridges.inverse_map_set`

— Function`inverse_map_set(::Type{BT}, set) where {BT}`

Return the preimage of `set`

through the linear map `A`

defined in `Variable.SetMapBridge`

and `Constraint.SetMapBridge`

. This is used for getting the `MathOptInterface.ConstraintSet`

.

`MathOptInterface.Bridges.map_function`

— Function`map_function(::Type{BT}, func) where {BT}`

Return the image of `func`

through the linear map `A`

defined in `Variable.SetMapBridge`

and `Constraint.SetMapBridge`

. This is used for getting the `MathOptInterface.ConstraintPrimal`

of variable bridges. For constraint bridges, this is used for bridging the constraint, setting the `MathOptInterface.ConstraintFunction`

and `MathOptInterface.ConstraintPrimalStart`

and modifying the function with `MathOptInterface.modify`

.

`map_function(::Type{BT}, func, i::IndexInVector) where {BT}`

Return the scalar function at the `i`

th index of the vector function that would be returned by `map_function(BT, func)`

except that it may compute the `i`

th element. This is used by `bridged_function`

and for getting the `MathOptInterface.VariablePrimal`

and `MathOptInterface.VariablePrimalStart`

of variable bridges.

`MathOptInterface.Bridges.inverse_map_function`

— Function`inverse_map_function(::Type{BT}, func) where {BT}`

Return the image of `func`

through the inverse of the linear map `A`

defined in `Variable.SetMapBridge`

and `Constraint.SetMapBridge`

. This is used by `Variable.unbridged_map`

and for setting the `MathOptInterface.VariablePrimalStart`

of variable bridges and for getting the `MathOptInterface.ConstraintFunction`

, the `MathOptInterface.ConstraintPrimal`

and the `MathOptInterface.ConstraintPrimalStart`

of constraint bridges.

`MathOptInterface.Bridges.adjoint_map_function`

— Function`adjoint_map_function(::Type{BT}, func) where {BT}`

Return the image of `func`

through the adjoint of the linear map `A`

defined in `Variable.SetMapBridge`

and `Constraint.SetMapBridge`

. This is used for getting the `MathOptInterface.ConstraintDual`

and `MathOptInterface.ConstraintDualStart`

of constraint bridges.

`MathOptInterface.Bridges.inverse_adjoint_map_function`

— Function`inverse_adjoint_map_function(::Type{BT}, func) where {BT}`

Return the image of `func`

through the inverse of the adjoint of the linear map `A`

defined in `Variable.SetMapBridge`

and `Constraint.SetMapBridge`

. This is used for getting the `MathOptInterface.ConstraintDual`

of variable bridges and setting the `MathOptInterface.ConstraintDualStart`

of constraint bridges.

## Bridging graph API

`MathOptInterface.Bridges.Graph`

— Type`Graph()`

A type-stable datastructure for computing the shortest hyperpath problem.

**Nodes**

There are three types of nodes in the graph:

Add nodes to the graph using `add_node`

.

**Edges**

There are two types of edges in the graph:

Add edges to the graph using `add_edge`

.

For the ability to add a variable constrained on creation as a free variable followed by a constraint, use `set_variable_constraint_node`

.

**Optimal hyper-edges**

Use `bridge_index`

to compute the minimum-cost bridge leaving a node.

Note that `bridge_index`

lazy runs a Bellman-Ford algorithm to compute the set of minimum cost edges. Thus, the first call to `bridge_index`

after adding new nodes or edges will take longer than subsequent calls.

`MathOptInterface.Bridges.VariableNode`

— Type`VariableNode(index::Int)`

A node in `Graph`

representing a variable constrained on creation.

`MathOptInterface.Bridges.ConstraintNode`

— Type`ConstraintNode(index::Int)`

A node in `Graph`

representing a constraint.

`MathOptInterface.Bridges.ObjectiveNode`

— Type`ObjectiveNode(index::Int)`

A node in `Graph`

representing an objective function.

`MathOptInterface.Bridges.Edge`

— Type```
Edge(
bridge_index::Int,
added_variables::Vector{VariableNode},
added_constraints::Vector{ConstraintNode},
)
```

Return a new datastructure representing an edge in `Graph`

that starts at a `VariableNode`

or a `ConstraintNode`

.

`MathOptInterface.Bridges.ObjectiveEdge`

— Type```
ObjectiveEdge(
bridge_index::Int,
added_variables::Vector{VariableNode},
added_constraints::Vector{ConstraintNode},
)
```

Return a new datastructure representing an edge in `Graph`

that starts at an `ObjectiveNode`

.

`MathOptInterface.Bridges.add_node`

— Function```
add_node(graph::Graph, ::Type{VariableNode})::VariableNode
add_node(graph::Graph, ::Type{ConstraintNode})::ConstraintNode
add_node(graph::Graph, ::Type{ObjectiveNode})::ObjectiveNode
```

Add a new node to `graph`

.

`MathOptInterface.Bridges.add_edge`

— Function```
add_edge(graph::Graph, node::VariableNode, edge::Edge)::Nothing
add_edge(graph::Graph, node::ConstraintNode, edge::Edge)::Nothing
add_edge(graph::Graph, node::ObjectiveNode, edge::ObjectiveEdge)::Nothing
```

Add `edge`

to `graph`

, where `edge`

starts at `node`

and connects to the nodes defined in `edge`

.

`MathOptInterface.Bridges.set_variable_constraint_node`

— Function```
set_variable_constraint_node(
graph::Graph,
variable_node::VariableNode,
constraint_node::ConstraintNode,
cost::Int,
)
```

As an alternative to `variable_node`

, add a virtual edge to `graph`

that represents adding a free variable, followed by a constraint of type `constraint_node`

, with bridging cost `cost`

.

**Why is this needed?**

Variables can either be added as a variable constrained on creation, or as a free variable which then has a constraint added to it.

`MathOptInterface.Bridges.bridge_index`

— Function```
bridge_index(graph::Graph, node::VariableNode)::Int
bridge_index(graph::Graph, node::ConstraintNode)::Int
bridge_index(graph::Graph, node::ObjectiveNode)::Int
```

Return the optimal index of the bridge to chose from `node`

.

`MathOptInterface.Bridges.is_variable_edge_best`

— Function`is_variable_edge_best(graph::Graph, node::VariableNode)::Bool`

Return a `Bool`

indicating whether `node`

should be added as a variable constrained on creation, or as a free variable followed by a constraint.