# Crate optimization_engine[−][src]

Expand description

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

Augmented Lagrangian and Penalty Methods

Constraints and projections

Optimisation algorithms

Estimates a local Lipschitz constant for a mapping $F: \mathbb{R}^n \to \mathbb{R}^n$

matrix_operations

## Enums

Exceptions/Errors that may arise while solving a problem

## Type Definitions

Result of a function call (status)