Uncertainty reduction in robust optimization
Résumé
Uncertainty reduction has recently been introduced in the robust optimization literature as a relevant special case of decision-dependent uncertainty.
Herein, we identify two relevant situations in which the problem is polynomially solvable. We further provide insights into possible MILP reformulations and the strength of their continuous relaxations.
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