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作者:

Sheng, Haiyun (Sheng, Haiyun.) | Du, Donglei (Du, Donglei.) | Sun, Yuefang (Sun, Yuefang.) | Sun, Jian (Sun, Jian.) | Zhang, Xiaoyan (Zhang, Xiaoyan.)

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EI

摘要:

Cover problem is a typical NP-hard problem, which has comprehensive application background and is a hot topic in recent years. In this paper, we study two stage, finite scenarios stochastic versions of set cover problem with submodular penalties which is the generalization of the stochastic vertex cover problem with submodular penalties. The goal is to minimize the sum of the first stage cost, the expected second stage cost and the expected penalty cost. By doing some research on the structural properties of submodular function, we present a primal-dual (Formula Presented)-approximation algorithm for the stochastic set cover problem with submodular penalties (4-approximation algorithm for the stochastic vertex cover problem with submodular penalties when (Formula Presented)), where (Formula Presented) is the maximum frequency of the element in the family of subsets. © 2020, Springer Nature Switzerland AG.

关键词:

Approximation algorithms NP-hard Stochastic systems

作者机构:

  • [ 1 ] [Sheng, Haiyun]School of Mathematical Science and Institute of Mathematics, Nanjing Normal University, Nanjing; Jiangsu; 210023, China
  • [ 2 ] [Du, Donglei]Faculty of Management, University of New Brunswick, Fredericton; NB; E3B 5A3, Canada
  • [ 3 ] [Sun, Yuefang]School of Mathematical Information, Shaoxing University, Shaoxing; Zhejiang; 312000, China
  • [ 4 ] [Sun, Jian]Department of Operations Research and Information Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Zhang, Xiaoyan]School of Mathematical Science and Institute of Mathematics, Nanjing Normal University, Nanjing; Jiangsu; 210023, China

通讯作者信息:

  • [zhang, xiaoyan]school of mathematical science and institute of mathematics, nanjing normal university, nanjing; jiangsu; 210023, china

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ISSN: 0302-9743

年份: 2020

卷: 12290 LNCS

页码: 37-48

语种: 英文

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WoS核心集被引频次: 0

SCOPUS被引频次: 1

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