arXiv:2003.00292 [math.OC]AbstractReferencesReviewsResources
OpEn: Code Generation for Embedded Nonconvex Optimization
Pantelis Sopasakis, Emil Fresk, Panagiotis Patrinos
Published 2020-02-29Version 1
We present Optimization Engine (OpEn): an open-source code generation tool for real-time embedded nonconvex optimization, which implements a novel numerical method. OpEn combines the proximal averaged Newton-type method for optimal control (PANOC) with the penalty and augmented Lagrangian methods to compute approximate stationary points of nonconvex problems. The proposed method involves very simple algebraic operations such as vector products, has a low memory footprint and exhibits very good convergence properties that allow the solution of nonconvex problems on embedded devices. OpEn's core solver is written is Rust - a modern, high-performance, memory-safe and thread-safe systems programming language - while users can call it from Python, MATLAB, C, C++ or over a TCP socket.