The paper defines the ambiguity premium Δ_ε(x) as the gap between pessimistic and optimistic upper-level values over ε-optimal follower responses and provides bounds plus a screening workflow to trace robustness-efficiency frontiers in bilevel problems.
A damage-structured pde model of stem cell hierarchies: The dual role of dedifferentiation in tissue homeostasis and aging.Plos one, 21(2):e0335163, 2026
3 Pith papers cite this work. Polarity classification is still indexing.
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The notes explain the failure of classical NLP optimality conditions for MPECs and outline multiplier-based, implicit-programming, and piecewise-programming viewpoints with emphasis on critical cones and strong regularity.
Workshop notes explain the hypotheses required for first-order optimality conditions in MPECs and how to classify models and prove those hypotheses in practice.
citing papers explorer
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A Diagnostic Framework for Implementation Risk in Bilevel Decision Problems: The Ambiguity Premium and the Robustness--Efficiency Frontier
The paper defines the ambiguity premium Δ_ε(x) as the gap between pessimistic and optimistic upper-level values over ε-optimal follower responses and provides bounds plus a screening workflow to trace robustness-efficiency frontiers in bilevel problems.
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Optimization Workshop Notes for Mathematical Programming with Equilibrium Constraints (MPECs): Second-Order Optimality Conditions
The notes explain the failure of classical NLP optimality conditions for MPECs and outline multiplier-based, implicit-programming, and piecewise-programming viewpoints with emphasis on critical cones and strong regularity.
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Optimization Workshop Notes for Mathematical Programming with Equilibrium Constraints (MPECs): Verification of MPEC Hypotheses
Workshop notes explain the hypotheses required for first-order optimality conditions in MPECs and how to classify models and prove those hypotheses in practice.