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Robust bilevel optimization for near-optimal lower-level solutions

Mathieu Besançon, Miguel F. Anjos and Luce Brotcorne

Article (2024)

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Abstract

Bilevel optimization problems embed the optimality of a subproblem as a constraint of another optimization problem. We introduce the concept of near-optimality robustness for bilevel optimization, protecting the upper-level solution feasibility from limited deviations from the optimal solution at the lower level. General properties and necessary conditions for the existence of solutions are derived for near-optimal robust versions of general bilevel optimization problems. A duality-based solution method is defined when the lower level is convex, leveraging the methodology from the robust and bilevel literature. Numerical results assess the efficiency of exact and heuristic methods and the impact of valid inequalities on the solution time

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Department: Department of Mathematics and Industrial Engineering
Research Center: GERAD - Research Group in Decision Analysis
PolyPublie URL: https://publications.polymtl.ca/65063/
Journal Title: Journal of Global Optimization (vol. 90)
Publisher: Springer Nature
DOI: 10.1007/s10898-024-01422-z
Official URL: https://doi.org/10.1007/s10898-024-01422-z
Date Deposited: 09 May 2025 09:38
Last Modified: 20 Mar 2026 20:00
Cite in APA 7: Besançon, M., Anjos, M. F., & Brotcorne, L. (2024). Robust bilevel optimization for near-optimal lower-level solutions. Journal of Global Optimization, 90, 813-842. https://doi.org/10.1007/s10898-024-01422-z

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