Journal: Mathematical Programming Computation

Abbreviation

Math. Prog. Comp

Publisher

Springer

Journal Volumes

ISSN

1867-2957
1867-2949

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2018 - 201912020 - 20222
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Publications 1 - 3 of 3
  • RBFOpt: an open-source library for black-box optimization with costly function evaluations
    Item type: Journal Article
    Costa, Alberto; Nannicini, Giacomo (2018)
    Mathematical Programming Computation
  • OSQP: an operator splitting solver for quadratic programs
    Item type: Journal Article
    Stellato, Bartolomeo; Banjac, Goran; Goulart, Paul; et al. (2020)
    Mathematical Programming Computation
    We present a general-purpose solver for convex quadratic programs based on the alternating direction method of multipliers, employing a novel operator splitting technique that requires the solution of a quasi-definite linear system with the same coefficient matrix at almost every iteration. Our algorithm is very robust, placing no requirements on the problem data such as positive definiteness of the objective function or linear independence of the constraint functions. It can be configured to be division-free once an initial matrix factorization is carried out, making it suitable for real-time applications in embedded systems. In addition, our technique is the first operator splitting method for quadratic programs able to reliably detect primal and dual infeasible problems from the algorithm iterates. The method also supports factorization caching and warm starting, making it particularly efficient when solving parametrized problems arising in finance, control, and machine learning. Our open-source C implementation OSQP has a small footprint, is library-free, and has been extensively tested on many problem instances from a wide variety of application areas. It is typically ten times faster than competing interior-point methods, and sometimes much more when factorization caching or warm start is used. OSQP has already shown a large impact with tens of thousands of users both in academia and in large corporations. © 2020 Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society.
  • acados-a modular open-source framework for fast embedded optimal control
    Item type: Journal Article
    Verschueren, Robin; Frison, Gianluca; Kouzoupis, Dimitris; et al. (2022)
    Mathematical Programming Computation
    This paper presents the acados software package, a collection of solvers for fast embedded optimization intended for fast embedded applications. Its interfaces to higher-level languages make it useful for quickly designing an optimization-based control algorithm by putting together different algorithmic components that can be readily connected and interchanged. Since the core of acados is written on top of a high-performance linear algebra library, we do not sacrifice computational performance. Thus, we aim to provide both flexibility and performance through modularity, without the need to rely on automatic code generation, which facilitates maintainability and extensibility. The main features of acados are: efficient optimal control algorithms targeting embedded devices implemented in C, linear algebra based on the high-performance BLASFEO Frison (ACM Transactions on Mathematical Software (TOMS) 44: 1-30, 2018) library, user-friendly interfaces to Matlab and Python, and compatibility with the modeling language of CasADi Andersson (Mathematical Programming Computation 11: 136, 2019). acados is free and open-source software released under the permissive BSD 2-Clause license.
Publications 1 - 3 of 3