HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Complexity of near-optimal robust versions of multilevel optimization problems

Mathieu Besançon 1 Miguel Anjos 2 Luce Brotcorne 3
3 INOCS - Integrated Optimization with Complex Structure
Inria Lille - Nord Europe, ULB - Université libre de Bruxelles, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : 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 decisionmakers. 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.
Document type :
Preprints, Working Papers, ...
Complete list of metadata

Contributor : Mathieu Besançon Connect in order to contact the contributor
Submitted on : Monday, February 22, 2021 - 5:16:36 PM
Last modification on : Thursday, March 24, 2022 - 3:43:41 AM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License


  • HAL Id : hal-03149050, version 1
  • ARXIV : 2011.00824


Mathieu Besançon, Miguel Anjos, Luce Brotcorne. Complexity of near-optimal robust versions of multilevel optimization problems. 2021. ⟨hal-03149050⟩



Record views


Files downloads