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作者:

Zhang, Zhen-Ning (Zhang, Zhen-Ning.) | Du, Dong-Lei (Du, Dong-Lei.) | Ma, Ran (Ma, Ran.) | Wu, Dan (Wu, Dan.)

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摘要:

In this paper, we investigate the maximization of the differences between a nonnegative monotone diminishing return submodular (DR-submodular) function and a nonnegative linear function on the integer lattice. As it is almost unapproximable for maximizing a submodular function without the condition of nonnegative, we provide weak (bifactor) approximation algorithms for this problem in two online settings, respectively. For the unconstrained online model, we combine the ideas of single-threshold greedy, binary search and function scaling to give an efficient algorithm with a 1/2 weak approximation ratio. For the online streaming model subject to a cardinality constraint, we provide a one-pass (3-5)/2 weak approximation ratio streaming algorithm. Its memory complexity is (klogk/Ε), and the update time for per element is (log2k/Ε). © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词:

Approximation algorithms Operations research

作者机构:

  • [ 1 ] [Zhang, Zhen-Ning]Department of Operations Research and Information Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Du, Dong-Lei]Faculty of Management, University of New Brunswick, Fredericton; NB; E3B 9Y2, Canada
  • [ 3 ] [Ma, Ran]School of Management Engineering, Qingdao University of Technology, Shandong, Qingdao; 266525, China
  • [ 4 ] [Wu, Dan]School of Mathematics and Statistics, Henan University of Science and Technology, Henan, Luoyang; 471023, China

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来源 :

Journal of the Operations Research Society of China

ISSN: 2194-668X

年份: 2024

期: 3

卷: 12

页码: 795-807

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