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User visible changes in PRIMA.jl

Version 0.2.0

  • General method prima(f, x0; kwds...) which solves the problem with the most suitable Powell's algorithm (among COBYLA, LINCOA, BOBYQA, or NEWUOA) depending on the constraints imposed via the keywords kwds....

  • Objective function and non-linear constraints for cobyla:

    • Non-linear equality constraints can be specified by keyword nonlinear_eq.
    • The objective function is called as f(x) like in other algorithms.
    • The functions implementing the non-linear constraints are passed by keywords nonlinear_eq and nonlinear_ineq.

  • Algorithms have a more similar interface:

    • All algorithms have the same positional input, only the available keywords may change.
    • All algorithms have the same convention for the objective function. Non-linear constraints, if any, are provided by other user-defined functions.
    • All algorithms yield a 2-tuple (x,info) with x an approximate solution (provided algorithm was successful) and info a structured object collecting other outputs from the algorithm. The following properties are available for all algorithms: info.fx is the objective function value f(x), info.nf is the number of evaluations of the objective function, and info.status is the termination status of the algorithm.
    • issuccess(info) yields whether algorithm was successful.
    • PRIMA.reason(info) yields a textual description of the termination status of the algorithm.

  • Scaling of the variables: the variables x ∈ ℝⁿ may be scaled by the scaling factors provided by the caller via keywords scale to re-express the problem in the scaled variables u ∈ ℝⁿ such that u[i] = x[i]/scale[i]. Note that the objective function, the constraints (linear and non-linear), and the bounds remain specified in the variables. Scaling the variables is useful to improve the conditioning of the problem, to make the scaled variables u having approximately the same magnitude, and to adapt to heterogeneous variables or with different units.

Version 0.1.1

  • Keywords for other constraints than bounds have been renamed as nonlinear_ineq for non-linear inequality constraints, linear_ineq for linear inequality constraints, and linear_eq for linear equality constraints.

  • In cobyla, if the caller is not interested in the values of c(x) expressing the non-linear inequality constraints, the number of such constraints may be provided instead of the array to store c(x).

Version 0.1.0

First public version.