Conference item
COSMO: A conic operator splitting method for large convex problems
- Abstract:
- This paper describes the Conic Operator Splitting Method (COSMO), an operator splitting algorithm for convex optimisation problems with quadratic objective function and conic constraints. At each step the algorithm alternates between solving a quasi-definite linear system with a constant coefficient matrix and a projection onto convex sets. The solver is able to exploit chordal sparsity in the problem data and to detect infeasible problems. The low per-iteration computational cost makes the method particularly efficient for large problems, e.g. semidefinite programs in portfolio optimisation, graph theory, and robust control. Our Julia implementation is open-source, extensible, integrated into the Julia optimisation ecosystem and performs well on a variety of large convex problem classes.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 259.0KB, Terms of use)
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- Publisher copy:
- 10.23919/ECC.2019.8796161
Authors
- Publisher:
- IEEE
- Host title:
- 2019 18th European Control Conference (ECC)
- Pages:
- 1951-1956
- Publication date:
- 2019-08-15
- Acceptance date:
- 2019-02-20
- Event title:
- European Control Conference 2019 (ECC 19)
- Event location:
- Naples, Italy
- Event website:
- https://ecc19.eu
- Event start date:
- 2019-06-25
- Event end date:
- 2019-06-28
- DOI:
- EISBN:
- 9783907144008
- ISBN:
- 9783907144015
- Language:
-
English
- Pubs id:
-
pubs:976034
- UUID:
-
uuid:25211347-1646-4d6b-9ad5-807d1c865e50
- Local pid:
-
pubs:976034
- Source identifiers:
-
976034
- Deposit date:
-
2019-03-16
Terms of use
- Copyright holder:
- EUCA
- Copyright date:
- 2019
- Rights statement:
- © 2019 EUCA.
- Notes:
- This is the accepted manuscript version of the paper. The final version is available online from IEEE at https://dx.doi.org/10.23919/ECC.2019.8796161
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