The Greedy Algorithm and Its Performance Guarantees for Solving Maximization of Submodular Function

Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 686)

Abstract

Maximizing or minimizing submodular function is widely used in combinatorial optimization problems. In this paper; we present an approximation algorithm for maximizing submodular function subject to independence system that be represented as the intersection of a limited number of matroids, and discuss its performance guarantee.

Keywords

Combinatorial optimization problems Submodular function Performance guarantee Approximation algorithm 
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References

  1. 1.
    M Suiridendo A.1.5282-approximation algorithm for metric uncapacitated facility location problem. Proceeding Integer Programming and Combinatorial Optimization. Cambridge, MA, USA, 458 (2002)Google Scholar
  2. 2.
    Fisher, M.L., Nemhauer, G.L., Wolsey, L.A.: An analysis of approximations for maxing sub Modular set functions programming study, 8, 73–87 (1978)Google Scholar
  3. 3.
    Gao, Y., Hao, Z., He, S.: An approximate algorithm for solving the maximum value of the function of non-increasing modulus function and its performance guarantee. Pract. Underst. Mathe. 12(38), 148–149 (2008)Google Scholar
  4. 4.
    Narayanan, H.: Submodular functions and electrical networks. Vehicles: North Holland (1997)Google Scholar
  5. 5.
    Wang, W., Zhang, F., TuoXiaoli, He, S.: Local search algorithm for solving maximizing submodular set function. J. Wenzhou University (3) 2008Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.School of ScienceAir Force Engineering UniversityXi’anChina

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