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A proximal bundle method based on approximate subgradients
journal contribution
posted on 2023-06-07, 20:32 authored by Michael HintermuellerIn this paper a proximal bundle method is introduced that is capable to deal with approximate subgradients. No further knowledge of the approximation quality (like explicit knowledge or controllability of error bounds) is required for proving convergence. It is shown that every accumulation point of the sequence of iterates generated by the proposed algorithm is a well-defined approximate solution of the exact minimization problem. In the case of exact subgradients the algorithm behaves like well-established proximal bundle methods. Numerical tests emphasize the theoretical findings.
History
Publication status
- Published
Journal
Computational Optimization and ApplicationsISSN
0926-6003Publisher
Springer VerlagExternal DOI
Issue
3Volume
20Page range
245-266Department affiliated with
- Mathematics Publications
Full text available
- No
Peer reviewed?
- Yes