Struct OptimizationProblem 

pub struct OptimizationProblem<const DIM: usize, C: ConstraintState = Unconstrained, O: ObjectiveState = SingleObjective, V: ConvexityState = NonConvex, M: ManifoldState = Euclidean> { /* private fields */ }

Optimization problem with compile-time properties

This type encodes optimization problem characteristics at compile time, enabling the type system to enforce correct usage of optimization algorithms.

Type Parameters

• DIM - Problem dimension (number of parameters)
• C - Constraint state (Unconstrained or Constrained)
• O - Objective state (SingleObjective or MultiObjective)
• V - Convexity state (Convex or NonConvex)
• M - Manifold state (Euclidean, Riemannian, or Statistical)

Examples

use amari_optimization::phantom::*;

// Unconstrained, single-objective, convex problem in Euclidean space
type ConvexProblem = OptimizationProblem<10, Unconstrained, SingleObjective, Convex, Euclidean>;

// Multi-objective problem on a statistical manifold
type MultiObjectiveStats = OptimizationProblem<5, Unconstrained, MultiObjective, NonConvex, Statistical>;

Implementations

impl<const DIM: usize, C: ConstraintState, O: ObjectiveState, V: ConvexityState, M: ManifoldState> OptimizationProblem<DIM, C, O, V, M>

pub fn new() -> Self

Create a new optimization problem with given properties

pub const fn dimension(&self) -> usize

Get the problem dimension

impl<const DIM: usize, O: ObjectiveState, V: ConvexityState, M: ManifoldState> OptimizationProblem<DIM, Unconstrained, O, V, M>

pub fn with_constraints(self) -> OptimizationProblem<DIM, Constrained, O, V, M>

Add constraints to an unconstrained problem

impl<const DIM: usize, C: ConstraintState, V: ConvexityState, M: ManifoldState> OptimizationProblem<DIM, C, SingleObjective, V, M>

pub fn with_multiple_objectives( self, ) -> OptimizationProblem<DIM, C, MultiObjective, V, M>

Convert to multi-objective problem

impl<const DIM: usize, C: ConstraintState, O: ObjectiveState, M: ManifoldState> OptimizationProblem<DIM, C, O, NonConvex, M>

pub fn assume_convex(self) -> OptimizationProblem<DIM, C, O, Convex, M>

Mark problem as convex (if verified)

impl<const DIM: usize, C: ConstraintState, O: ObjectiveState, V: ConvexityState> OptimizationProblem<DIM, C, O, V, Euclidean>

pub fn on_riemannian_manifold( self, ) -> OptimizationProblem<DIM, C, O, V, Riemannian>

Specify optimization on Riemannian manifold

pub fn on_statistical_manifold( self, ) -> OptimizationProblem<DIM, C, O, V, Statistical>

Specify optimization on statistical manifold

Trait Implementations

impl<const DIM: usize, C: Clone + ConstraintState, O: Clone + ObjectiveState, V: Clone + ConvexityState, M: Clone + ManifoldState> Clone for OptimizationProblem<DIM, C, O, V, M>

fn clone(&self) -> OptimizationProblem<DIM, C, O, V, M>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<const DIM: usize, C: Debug + ConstraintState, O: Debug + ObjectiveState, V: Debug + ConvexityState, M: Debug + ManifoldState> Debug for OptimizationProblem<DIM, C, O, V, M>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<const DIM: usize, C: ConstraintState, O: ObjectiveState, V: ConvexityState, M: ManifoldState> Default for OptimizationProblem<DIM, C, O, V, M>

fn default() -> Self

Returns the “default value” for a type.