Maximizing Submodular Functions under Matroid Constraints by Evolutionary Algorithms

Many combinatorial optimization problems have underlying goal functions that are submodular. The classical goal is to find a good solution for a given submodular function f under a given set of constraints. In this paper, we investigate the runtime of a simple single objective evolutionary algorithm...

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Bibliographic Details

Published in:	Evolutionary computation Vol. 23; no. 4; pp. 543 - 558
Main Authors:	Friedrich, Tobias, Neumann, Frank
Format:	Journal Article
Language:	English
Published:	United States 01.12.2015
Subjects:	Algorithms Biological Evolution Computational Biology Computer Simulation Humans Models, Statistical multiobjective optimization approximation maximum cut Submodular functions matroid constraints runtime hypervolume indicator theory
ISSN:	1530-9304
Online Access:	Get more information
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