JuMP model optimisation

PortfolioOptimisers.jl is based on JuMP, as such it tries to be as flexible as possible.

These types and functions let us define solver and solution interfaces.

PortfolioOptimisers.Dict_VecPair Type

const Dict_VecPair = Union{<:AbstractDict, <:AbstractVector{<:Pair}}

Alias for a dictionary or vector of pairs.

Represents solver settings as either a dictionary mapping constraint attributes to values, or a vector of pairs where the first element is a constraint attribute and the second is its value. Used for passing attribute settings to JuMP solvers.

Related

• SlvSettings

• Solver

• set_solver_attributes

source

PortfolioOptimisers.SlvSettings Type

const SlvSettings = Union{<:Pair, <:Dict_VecPair}

Alias for solver settings used in JuMP-based optimisation.

Represents solver settings as either a single solver attribute, or a collection of solver attributes.

Related

• Dict_VecPair

• Solver

• set_solver_attributes

source

PortfolioOptimisers.Solver Type

struct Solver{__T_name, __T_solver, __T_settings, __T_check_sol, __T_add_bridges} <: AbstractEstimator

Container for configuring a JuMP solver and its settings.

The Solver struct encapsulates all information needed to set up and run a JuMP optimisation, including the solver backend, solver-specific settings, solution checks, and bridge options.

Fields

• name: Symbol or string identifier for logging purposes.

• solver: The optimizer_factory in set_optimizer.

• settings: Optional solver-specific settings used in set_attribute.

• check_sol: Named tuple of solution for keyword arguments in assert_is_solved_and_feasible.

• add_bridges: The add_bridges keyword argument in set_optimizer.

Constructors

Solver(;
    name::Sym_Str = "",
    solver::Any = nothing,
    settings::Option{<:SlvSettings} = nothing,
    check_sol::NamedTuple = (;),
    add_bridges::Bool = true
) -> Solver

Keywords correspond to the struct's fields.

Validation

• If not nothing, !isempty(settings).

Examples

julia> Solver()
Solver
         name ┼ String: ""
       solver ┼ nothing
     settings ┼ nothing
    check_sol ┼ @NamedTuple{}: NamedTuple()
  add_bridges ┴ Bool: true

Related

• optimise_JuMP_model!

• set_optimizer

• set_attribute

• Sym_Str

• Option

• SlvSettings

source

PortfolioOptimisers.VecSlv Type

const VecSlv = AbstractVector{<:Solver}

Alias for a vector of Solver objects.

Represents a collection of solver configurations to be used in JuMP-based optimisation routines. Enables sequential or fallback solver strategies by passing multiple solver setups.

Related

• Solver

source

PortfolioOptimisers.Slv_VecSlv Type

const Slv_VecSlv = Union{<:Solver, <:VecSlv}

Alias for a single Solver or a vector of Solver objects.

Represents either a single solver configuration or a collection of solver configurations for JuMP-based optimisation routines. Enables flexible dispatch for optimisation functions that accept one or multiple solvers.

Related

• Solver

• VecSlv

source

PortfolioOptimisers.AbstractJuMPResult Type

abstract type AbstractJuMPResult <: AbstractResult

Abstract supertype for all JuMP-based optimisation result types in PortfolioOptimisers.jl.

All concrete and/or abstract types representing the result of a JuMP model optimisation should be subtypes of AbstractJuMPResult.

Related

• JuMPResult

source

PortfolioOptimisers.JuMPResult Type

struct JuMPResult{__T_trials, __T_success} <: AbstractJuMPResult

Result type for JuMP model optimisation.

The JuMPResult struct records the outcome of a JuMP optimisation, including trial errors and success status.

Fields

• trials: Dictionary of solver trials and errors.

• success: Boolean indicating whether optimisation succeeded.

Constructors

JuMPResult(;
    trials::AbstractDict,
    success::Bool
) -> JuMPResult

Keywords correspond to the struct's fields.

Examples

julia> JuMPResult(; trials = Dict(:HiGHS => Dict(:optimize! => "error")), success = true)
JuMPResult
   trials ┼ Dict{Symbol, Dict{Symbol, String}}: Dict(:HiGHS => Dict(:optimize! => "error"))
  success ┴ Bool: true

Related

• optimise_JuMP_model!

source

PortfolioOptimisers.set_solver_attributes Function

set_solver_attributes(args...)

Set solver attributes for a JuMP model.

This is a generic fallback that does nothing if no model or settings are provided.

Arguments

• args...: Arguments (ignored).

Returns

• nothing.

source

set_solver_attributes(model::JuMP.Model, settings::Dict_VecPair)

Set multiple solver attributes on a JuMP model.

Iterates over the provided settings and applies each as a solver attribute.

Arguments

• model: JuMP model.

• settings: Dictionary or vector of pairs of solver settings.

Returns

• nothing.

Related

• JuMP.Model

• set_attribute

• Dict_VecPair

source

set_solver_attributes(model::JuMP.Model, settings::Pair)

Set a single solver attribute on a JuMP model.

Arguments

• model: JuMP model.

• settings: Pair of attribute name and value.

Returns

• nothing.

Related

• JuMP.Model

• set_attribute

source

PortfolioOptimisers.optimise_JuMP_model! Function

optimise_JuMP_model!(model::JuMP.Model, slv::Slv_VecSlv)

Attempt to optimise a JuMP model using one or more configured solvers.

Tries each solver in order, applying settings and checking for solution feasibility. Returns a JuMPResult with trial errors and success status.

Arguments

• model: JuMP model to optimise.

• slv: Single Solver or vector of Solver objects.

Returns

• res::JuMPResult: Result object containing trial errors and success flag.

Details

• For each solver, sets the optimizer and attributes, runs JuMP.optimize!, and checks solution feasibility.

• If a solver fails, records the error and tries the next.

• Stops at the first successful solution.

Related

• JuMP.Model

• set_optimizer

• assert_is_solved_and_feasible

• set_solver_attributes

• JuMPResult

• Slv_VecSlv

source