Constrained Monotone k -Submodular Function Maximization Using Multiobjective Evolutionary Algorithms With Theoretical Guarantee

The problem of maximizing monotone <inline-formula> <tex-math notation="LaTeX">{k} </tex-math></inline-formula>-submodular functions under a size constraint arises in many applications, and it is NP-hard. In this paper, we propose a new approach which employs a mult...

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Bibliographic Details

Published in:	IEEE transactions on evolutionary computation Vol. 22; no. 4; pp. 595 - 608
Main Authors:	Qian, Chao, Shi, Jing-Cheng, Tang, Ke, Zhou, Zhi-Hua
Format:	Journal Article
Language:	English
Published:	IEEE 01.08.2018
Subjects:	Constrained optimization Electronic mail Evolutionary computation experimental studies Greedy algorithms Integrated circuit modeling Method of moments multiobjective evolutionary algorithms (MOEAs) Optimization submodular optimization theoretical analysis
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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