Using NLopt.jl

SemOptimizerNLopt implements the connection to NLopt.jl. It is only available if the NLopt package is loaded alongside StructuralEquationModel.jl in the running Julia session. It takes a bunch of arguments:

    •  algorithm: optimization algorithm

    •  options::Dict{Symbol, Any}: options for the optimization algorithm

    •  local_algorithm: local optimization algorithm

    •  local_options::Dict{Symbol, Any}: options for the local optimization algorithm

    •  equality_constraints::Vector{NLoptConstraint}: vector of equality constraints

    •  inequality_constraints::Vector{NLoptConstraint}: vector of inequality constraints

Constraints are explained in the section on Constrained optimization.

The defaults are LBFGS as the optimization algorithm and the standard options from NLopt.jl. We can choose something different:

using NLopt

my_optimizer = SemOptimizerNLopt(;
    algorithm = :AUGLAG,
    options = Dict(:maxeval => 200),
    local_algorithm = :LD_LBFGS,
    local_options = Dict(:ftol_rel => 1e-6)
)

This uses an augmented lagrangian method with LBFGS as the local optimization algorithm, stops at a maximum of 200 evaluations and uses a relative tolerance of the objective value of 1e-6 as the stopping criterion for the local algorithm.

To see how to use the optimizer to actually fit a model now, check out the Model fitting section.

In the NLopt docs, you can find explanations about the different algorithms and a tutorial that also explains the different options.

To choose an algorithm, just pass its name without the 'NLOPT_' prefix (for example, 'NLOPT_LD_SLSQP' can be used by passing algorithm = :LD_SLSQP).

The README of the julia package may also be helpful, and provides a list of options:

• algorithm
• stopval
• ftol_rel
• ftol_abs
• xtol_rel
• xtol_abs
• constrtol_abs
• maxeval
• maxtime
• initial_step
• population
• seed
• vector_storage