Constrained submodular maximization via greedy local search

Document Type

Article

Publication Date

1-1-2019

Abstract

We present a simple combinatorial [Formula presented]-approximation algorithm for maximizing a monotone submodular function subject to a knapsack and a matroid constraint. This classic problem is known to be hard to approximate within factor better than 1−1∕e. We extend the algorithm to yield [Formula presented] approximation for submodular maximization subject to a single knapsack and k matroid constraints, for any fixed k>1. Our algorithms, which combine the greedy algorithm of Khuller et al. (1999) and Sviridenko (2004) with local search, show the power of this natural framework in submodular maximization with combined constraints.

Identifier

85057186365 (Scopus)

Publication Title

Operations Research Letters

External Full Text Location

https://doi.org/10.1016/j.orl.2018.11.002

ISSN

01676377

First Page

1

Last Page

6

Issue

1

Volume

47

Grant

CCF-1445755

Fund Ref

National Science Foundation

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