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Many algorithms for maximizing a monotone submodular function subject to a knapsack constraint rely on the natural greedy heuristic.
Best algorithms for approximating the maximum of a submodular set function
G. L. Nemhauser and L. A. Wolsey · 1978
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An analysis of approximations for maximizing submodular set functions—i
George L Nemhauser, Laurence A Wolsey, and Marshall L Fisher · 1978
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Comparison theorems for differential equations
Alex McNabb · 1986
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A threshold of ln n for approximating set cover
Uriel Feige · 1998
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The budgeted maximum coverage problem
Samir Khuller, Anna Moss, and Joseph Naor · 1999
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A note on maximizing a submodular set function subject to a knapsack constraint
Maxim Sviridenko · 2004
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Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Thomas M. Cover and Joy A. Thomas · 2006
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Reuven Cohen and Liran Katzir · 2008
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K. Son, H. Kim, Y. Yi, and B. Krishnamachari · 2011
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Ordinary differential equations and dynamical systems
Thomas C Sideris · 2013
Fast algorithms for maximizing submodular functions
Ashwinkumar Badanidiyuru and Jan Vondrák · 2014
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A Nearly-Linear Time Algorithm for Submodular Maximization with a Knapsack Constraint
Alina Ene and Huy L. Nguyen · 2019
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A (1-e -1 {}^{\mbox{-1}} - ϵ \epsilon )-approximation for the monotone submodular multiple knapsack problem
Yaron Fairstein, Ariel Kulik, Joseph (Seffi) Naor, Danny Raz, and Hadas Shachnai · 2020
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Practical budgeted submodular maximization
Moran Feldman, Zeev Nutov, and Elad Shoham · 2020
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“bring your own greedy”+ max: Near-optimal 1/2-approximations for submodular knapsack
Grigory Yaroslavtsev, Samson Zhou, and Dmitrii Avdiukhin · 2020
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Cited alongside, same era.
Revisiting modified greedy algorithm for monotone submodular maximization with a knapsack constraint
Jing Tang, Xueyan Tang, Andrew Lim, Kai Han, Chongshou Li, and Junsong Yuan · 2021
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