On maximizing a monotone k-submodular function under a knapsack constraint
Abstract
We study the problem of maximizing a non-negative monotone k-submodular function f under a knapsack constraint, where a k-submodular function is a natural generalization of a submodular function to k dimensions. We present a deterministic (12-12e)≈ 0.316-approximation algorithm that evaluates f O(n4k3) times, based on the result of Sviridenko (2004) on submodular knapsack maximization.
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