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A mixed-integer approximation of robust optimization problems with mixed-integer adjustments
KTH, Numerisk analys, optimeringslära och systemteori.ORCID iD: 0000-0003-0299-5745
ABB Corporate Research Center, Ladenburg, Ladenburg, Germany.
KTH, Numerisk analys, optimeringslära och systemteori.ORCID iD: 0000-0002-5415-1715
2024 (English)In: Optimization and Engineering, ISSN 1389-4420, E-ISSN 1573-2924, Vol. 25, no 3, p. 1271-1296Article in journal (Refereed) Published
Abstract [en]

In the present article we propose a mixed-integer approximation of adjustable-robust optimization problems, that have both, continuous and discrete variables on the lowest level. As these trilevel problems are notoriously hard to solve, we restrict ourselves to weakly-connected instances. Our approach allows us to approximate, and in some cases exactly represent, the trilevel problem as a single-level mixed-integer problem. This allows us to leverage the computational efficiency of state-of-the-art mixed-integer programming solvers. We demonstrate the value of this approach by applying it to the optimization of power systems, particularly to the control of smart converters.

Place, publisher, year, edition, pages
Springer Nature , 2024. Vol. 25, no 3, p. 1271-1296
Keywords [en]
Adjustable Robustness, Mixed-Integer Optimization, Robust Optimization
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-213763DOI: 10.1007/s11081-023-09843-7ISI: 001118884300001Scopus ID: 2-s2.0-85173688367OAI: oai:DiVA.org:liu-213763DiVA, id: diva2:1959826
Available from: 2024-07-11 Created: 2025-05-21

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Kronqvist, JanRolfes, Jan

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