Multiple knapsack-constrained monotone DR-submodular maximization on distributive lattice

We consider a problem of maximizing a monotone DR-submodular function under multiple order-consistent knapsack constraints on a distributive lattice. Because a distributive lattice is used to represent a dependency constraint, the problem can represent a dependency constrained version of a submodula...

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Veröffentlicht in:Mathematical programming 2022-07, Vol.194 (1-2), p.85-119
Hauptverfasser: Maehara, Takanori, Nakashima, So, Yamaguchi, Yutaro
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Yamaguchi, Yutaro
description We consider a problem of maximizing a monotone DR-submodular function under multiple order-consistent knapsack constraints on a distributive lattice. Because a distributive lattice is used to represent a dependency constraint, the problem can represent a dependency constrained version of a submodular maximization problem on a set. We propose a ( [Formula omitted])-approximation algorithm for this problem. To achieve this result, we generalize the continuous greedy algorithm to distributive lattices: We choose a median complex as a continuous relaxation of the distributive lattice and define the multilinear extension on it. We show that the median complex admits special curves, named uniform linear motions. The multilinear extension of a DR-submodular function is concave along a positive uniform linear motion, which is a key property used in the continuous greedy algorithm.
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subjects Algorithms
Constraints
Greedy algorithms
Lattices
Maximization
Optimization
title Multiple knapsack-constrained monotone DR-submodular maximization on distributive lattice
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