Struct DefaultIterateInitializer 

pub struct DefaultIterateInitializer {
    pub bound_push: Number,
    pub bound_frac: Number,
    pub slack_bound_push: Number,
    pub slack_bound_frac: Number,
    pub constr_mult_init_max: Number,
    pub bound_mult_init_val: Number,
    pub bound_mult_init_method: String,
    pub eq_mult_calculator: Option<Box<dyn EqMultCalculator>>,
    pub least_square_init_primal: bool,
}

Fields

bound_push: Number

bound_frac: Number

slack_bound_push: Number

slack_bound_frac: Number

constr_mult_init_max: Number

bound_mult_init_val: Number

bound_mult_init_method: String

“constant” / “mu-based” / “least-square”.

eq_mult_calculator: Option<Box<dyn EqMultCalculator>>

Equality-multiplier calculator used by the least_square_mults step at the end of set_initial_iterates, matching upstream IpDefaultIterateInitializer.cpp:334-341. If None, the LS step is skipped (y_c, y_d remain at zero).

least_square_init_primal: bool

least_square_init_primal — port of IpDefaultIterateInitializer.cpp:200-222. When on, the initializer replaces the user’s starting x with the min-norm solution of the linearized equality + inequality constraints, then pushes that to the interior. Used by the Mehrotra cascade (IpIpoptAlg.cpp:182) to dramatically reduce iter-0 primal infeasibility on LP-shaped problems.

Implementations

impl DefaultIterateInitializer

pub fn new() -> Self

pub fn with_eq_mult_calculator(eq_mult: Box<dyn EqMultCalculator>) -> Self

pub fn push_to_interior( bound_push: Number, bound_frac: Number, x: Number, lower: Option<Number>, upper: Option<Number>, ) -> Number

Trait Implementations

impl Default for DefaultIterateInitializer

fn default() -> Self

Returns the “default value” for a type.

impl IterateInitializer for DefaultIterateInitializer

fn set_initial_iterates( &mut self, data: &IpoptDataHandle, cq: &IpoptCqHandle, nlp: &Rc<RefCell<dyn IpoptNlp>>, aug_solver: &mut dyn AugSystemSolver, ) -> bool

Populate IpoptData::curr with an initial iterate. Mirrors IterateInitializer::SetInitialIterates. The implementation can use aug_solver for least-square multiplier estimates; callers that don’t need that may pass any solver — concrete initializers consult it only if their option settings require it.