Journal
OPTIMIZATION LETTERS
Volume 15, Issue 8, Pages 2597-2610Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s11590-021-01754-9
Keywords
Near-optimal robustness; Multilevel optimization; Complexity theory
Funding
- GdR RO
- Mermoz scholarship
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The complexity of near-optimal robust multilevel problems is analyzed, showing that near-optimal robust versions of multilevel problems remain in the same complexity class as the original problems under general conditions.
Near-optimality robustness extends multilevel optimization with a limited deviation of a lower level from its optimal solution, anticipated by higher levels. We analyze the complexity of near-optimal robust multilevel problems, where near-optimal robustness is modelled through additional adversarial decision-makers. Near-optimal robust versions of multilevel problems are shown to remain in the same complexity class as the problem without near-optimality robustness under general conditions.
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