期刊文献+

求解多背包约束下下模集函数最大值的近似算法及其性能保证

Approximation Algorithm for Maximum of Submodular Set Function Subject to Multi-constraint Knapsack and Its Performance Guarantee
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摘要 将部分穷举法与贪婪算法相结合,给出求解多背包约束下非减下模集函数最大值的近似算法.证明了该算法的性能保证是1–e–1,算法的时间复杂性为O(3n4). A new approximation algorithm for maximum of a nondecreasing submodular set function subject to multi-constraint knapsack was given by combining partial exhaustive method with greedy algorithm. The performance guarantee of this algorithm is 1 - e^-1 and the time complexity of this algorithm is O(3n^4).
出处 《温州大学学报(自然科学版)》 2010年第1期6-10,共5页 Journal of Wenzhou University(Natural Science Edition)
关键词 下模集函数 贪婪算法 性能保证 背包约束 Submodular Set Function Greedy Algorithm Performance Guarantee Knapsack Constraint
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参考文献8

  • 1Fujishige S. Submodular functionsand optimization [M]. Amsterdam: North-Holland Press, 1991: 17-36.
  • 2Nernhauser G L, Wolsey L A, Fisher M L. An Analysis of approximations for maximizing submodular set function: I [J]. Mathematical Programming, 1978, 14: 265-294.
  • 3Sviridenko M. A note on maximizing a submodular set function subject to a knapsack constraint [J]. Operations Research Letters, 2004, 32(2): 41-43.
  • 4Wolsey L A. Maximising real-valued submodular functions:primal and dual heuristics for location problems [J]. Mathematics of Operations Research, 1982, 7:410-425.
  • 5Ilev V P. An approximation guarantee of the greedy descent algorithm for minimizing a submodular set function [J]. Discrete Applied Mathematics, 2001, 114: 131-146.
  • 6Khuller S, Moss A, Noar J. The budgeted maximum coverage problem [J]. Information Processing Letters, 1999, 70:39-45.
  • 7Lee J. Constrained maximum-entropy sampling [J]. Operations Research, 1998, 46: 655-664.
  • 8Chandra C, Amit K. Maximum coverage problem with group budget constraints and applications [J]. Lecture Note in Computer Science, 2004, 12:72-83.

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