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.
Exact and ap- proximate schemes for robust optimization problems with decision-dependent information discovery.INFORMS Journal on Computing, 37(6):1457–1477, 2025
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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.