solvr 0.2.0-beta.2

//! SLSQP (Sequential Least Squares Programming) algorithm trait.
use crate::DType;

use numr::error::Result;
use numr::runtime::Runtime;
use numr::tensor::Tensor;

use crate::optimize::error::OptimizeResult;

use super::types::{Bounds, ConstrainedOptions, ConstrainedResult, Constraint};

/// Trait for SLSQP constrained optimization.
pub trait SlsqpAlgorithms<R: Runtime<DType = DType>> {
    /// Sequential Least Squares Programming (SLSQP).
    ///
    /// Minimizes a scalar objective function subject to equality and inequality
    /// constraints using a sequential quadratic programming approach.
    ///
    /// # Arguments
    ///
    /// * `f` - Objective function f: R^n -> R
    /// * `x0` - Initial guess
    /// * `constraints` - Slice of nonlinear constraints
    /// * `bounds` - Variable bounds (optional lower/upper)
    /// * `options` - Algorithm options
    fn slsqp<F>(
        &self,
        f: F,
        x0: &Tensor<R>,
        constraints: &[Constraint<'_, R>],
        bounds: &Bounds<R>,
        options: &ConstrainedOptions,
    ) -> OptimizeResult<ConstrainedResult<R>>
    where
        F: Fn(&Tensor<R>) -> Result<f64>;
}