In the knapsack interdiction problem, there are $n$ items, each with a non-negative profit, interdiction cost, and packing weight. There is also an interdiction budget and a capacity. The objective is to select a set of items to interdict (delete) subject to the budget which minimizes the maximum profit attainable by packing the remaining items subject to the capacity. We present a $(2+ε)$-approximation running in $O(n^3ε^{-1}\log(ε^{-1}\log\sum_i p_i))$ time, where $p_i$ is the profit of item $i$. Although a polynomial-time approximation scheme (PTAS) is already known for this problem, our algorithm is considerably simpler and faster. The approach also generalizes naturally to a $(1+t+ε)$-approximation for $t$-dimensional knapsack interdiction with running time $O(n^{t+2}ε^{-1}\log(ε^{-1}\log\sum_i p_i))$. In computational experiments on standard benchmark instances with $ε=1$, our algorithm is on average within 0.4% of optimal and over 20 times faster than a state-of-the-art exact algorithm.

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