Network Relaxations for Discrete Bilevel Optimization under Linear Interactions

We investigate relaxations for a class of discrete bilevel programs where the interaction constraints linking the leader and the follower are linear. Our approach reformulates the upper-level optimality constraints by projecting the leader's decisions onto vectors that map to distinct follower...

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Veröffentlicht in:	arXiv.org 2024-07
Hauptverfasser:	Lozano, Leonardo, Bergman, David, Cire, Andre Augusto
Format:	Artikel
Sprache:	eng
Schlagworte:	Constraints Convexity Graphical representations Linear programming Mixed integer Optimization Solvers State vectors Upper bounds
Online-Zugang:	Volltext
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