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\geometry{margin=2cm} \geometry{margin=2cm}
\title{A Note on Interdiction of Linear Minimization Problems} \title{A Note on Interdiction of Linear Minimization Problems}
\author{Yu Cong \and Kangyi Tian}
\date{\today} \date{\today}
\DeclareMathOperator*{\opt}{OPT} \DeclareMathOperator*{\opt}{OPT}
@@ -40,26 +39,13 @@ The linear minimization interdiction problem considered here is
\begin{equation}\label{eq:interdiction} \begin{equation}\label{eq:interdiction}
\opt \opt
= =
\min_{\substack{S\in\mathcal F,\; R\subseteq S\\ c(R)\leq b}} \min \set{w(S\setminus R)\;|\;S\in\mathcal F,\; R\subseteq S,c(R)\leq b},
w(S\setminus R),
\end{equation} \end{equation}
where $c(R)=\sum_{e\in R}c(e)$. This is equivalent to first deleting an where $c(R)=\sum_{e\in R}c(e)$. This is equivalent to first deleting an
arbitrary set $R$ with $c(R)\leq b$ and then minimizing $w(S\setminus R)$ over arbitrary set $R$ with $c(R)\leq b$ and then minimizing $w(S\setminus R)$ over
$S\in\mathcal F$, because only $R\cap S$ affects the value of a chosen feasible $S\in\mathcal F$, because only $R\cap S$ affects the value of a chosen feasible
set $S$. set $S$.
Connectivity interdiction is the special case where $\mathcal F$ is the family
of cuts of a graph. In that case \eqref{eq:interdiction} is exactly the
$b$-free min-cut formulation
\[
\min_{\substack{\text{cut } C,\;R\subseteq C\\c(R)\leq b}}
w(C\setminus R).
\]
The argument below uses both minimization and linearity. Minimization gives the
near-minimizer certificate in \autoref{thm:two-approx-witness}; linearity gives
the truncation formula $w_\lambda(e)=\min\{w(e),\lambda c(e)\}$.
\section{Lagrangian relaxation} \section{Lagrangian relaxation}
It is helpful to first look at \eqref{eq:interdiction} as an integer program, It is helpful to first look at \eqref{eq:interdiction} as an integer program,