Trait OptimizationProblem 

pub trait OptimizationProblem<const N: usize> {
    type Input;
    type Output;
    type Error: Error + Send + Sync + 'static;

    // Required methods
    fn input(&self, x: &[f64; N]) -> Result<Self::Input, Self::Error>;
    fn objective(
        &self,
        input: &Self::Input,
        output: &Self::Output,
    ) -> Result<f64, Self::Error>;
}

Defines an optimization problem to be solved.

An optimization problem maps solver variables to a model input, then computes a scalar objective value from the model input and output.

The direction of optimization (minimize or maximize) is determined by the solver function chosen (e.g., golden_section::minimize vs golden_section::maximize).

The const generic N is the number of solver variables. For example, N = 1 represents a scalar optimization problem.

Required Associated Types

type Input

type Output

type Error: Error + Send + Sync + 'static

Required Methods

fn input(&self, x: &[f64; N]) -> Result<Self::Input, Self::Error>

Maps solver variables (x) into a model input.

Errors

Returns Self::Error if the input cannot be constructed from x.

fn objective( &self, input: &Self::Input, output: &Self::Output, ) -> Result<f64, Self::Error>

Computes a scalar objective value from model input/output.

The solver determines whether to minimize or maximize this objective.

Errors

Returns Self::Error if the objective cannot be computed.

Implementors