# [−][src]Crate optimization_engine

Optimization Engine is a framework for fast and accurate embedded nonconvex optimization.

Its core functionality (including all numerical routines) is written in Rust.

Optimization Engine can be used on PCs (all OSs are supported) and on embedded devices (e.g., Raspberry Pi, Atom, Odroid, etc).

Note that this is the API documentation of Optimization Engine; to get started, you would rather check out the documentation.

# Optimization Problems

Optimization Engine solves optimization problems of the general form

\begin{aligned} \mathrm{Minimize}\ f(u) \\ u \in U \\ F_1(u) \in C \\ F_2(u) = 0 \end{aligned}

where

• $u\in\mathbb{R}^{n_u}$ is the decision variable,
• $f:\mathbb{R}^n\to\mathbb{R}$ is a $C^{1,1}$-smooth cost function,
• $U$ is a (not necessarily convex) closed subset of $\mathbb{R}^{n_u}$ on which we can easily compute projections (e.g., a rectangle, a ball, a second-order cone, a finite set, etc),
• $F_1:\mathbb{R}^{n_u}\to\mathbb{R}^{n_1}$ and $F_2:\mathbb{R}^{n_u} \to\mathbb{R}^{n_2}$ are mappings with smooth partial derivatives, and
• $C\subseteq\mathbb{R}^{n_1}$ is a convex closed set on which we can easily compute projections.

## Re-exports

 pub use crate::core::fbs; pub use crate::core::panoc; pub use crate::core::AlgorithmEngine; pub use crate::core::Optimizer; pub use crate::core::Problem;

## Modules

 alm Augmented Lagrangian and Penalty Methods constraints Constraints and projections core Optimisation algorithms lipschitz_estimator Estimates a local Lipschitz constant for a mapping $F: \mathbb{R}^n \to \mathbb{R}^n$ matrix_operations matrix_operations

## Enums

 SolverError Exceptions/Errors that may arise while solving a problem