arXiv Analytics

Sign in

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.

Related articles: Most relevant | Search more
arXiv:2106.05206 [math.OC] (Published 2021-06-09)
Avoiding Traps in Nonconvex Problems
arXiv:1904.10546 [math.OC] (Published 2019-04-23)
Embedded nonlinear model predictive control for obstacle avoidance using PANOC
arXiv:1902.07815 [math.OC] (Published 2019-02-20)
Analysis of the alternating direction method of multipliers for nonconvex problems