MultistartOptimization
MultistartOptimization.MinimizationProblem
— Typestruct MinimizationProblem{F, T}
Wrapper for a minimization problem.
Fields
objective
The function to be minimized.
lower_bounds
Lower bounds (a vector of real numbers).
upper_bounds
Upper bounds (a vector of real numbers).
MultistartOptimization.LocationValue
— Typestruct LocationValue{T<:(AbstractArray{#s280,1} where #s280<:Real), S<:Real}
A location-value pair.
Fields
location
Location (a vector of real numbers).
value
The value of the objective at
location
.
MultistartOptimization.NLoptLocalMethod
— TypeNLoptLocalMethod(algorithm; options...)
A wrapper for algorithms supported by NLopt
. Used to construct the corresponding optimization problem.
See the NLopt documentation for the options. Defaults are changed slightly.
MultistartOptimization.local_minimization
— Functionlocal_minimization(local_method, minimization_problem, x)
Solve minimization_problem
using local_method
, starting from x
. Return a LocationValue
.
MultistartOptimization.TikTak
— TypeTikTak(quasirandom_N; keep_ratio, θ_min, θ_max, θ_pow)
The “TikTak” multistart method, as described in Arnoud, Guvenen, and Kleineberg (2019).
This implements the multistart part, can be called with arbitrary local methods, see multistart_minimization
.
Arguments
quasirandom_N
: the number of quasirandom points for the first pass (using a Sobol sequence).
Keyword arguments
keep_ratio
: the fraction of best quasirandom points which are keptθ_min
andθ_max
clamp the weight parameter,θ_pow
determines the power it is raised to.
The defaults are from the paper cited above.
MultistartOptimization.multistart_minimization
— Functionmultistart_minimization(multistart_method, local_method, minimization_problem)
Solve minimization_problem
by using local_method
within multistart_method
.