Mathematical Programming

, Volume 14, Issue 1, pp 265–294

An analysis of approximations for maximizing submodular set functions—I

  • G. L. Nemhauser
  • L. A. Wolsey
  • M. L. Fisher

DOI: 10.1007/BF01588971

Cite this article as:
Nemhauser, G.L., Wolsey, L.A. & Fisher, M.L. Mathematical Programming (1978) 14: 265. doi:10.1007/BF01588971


LetN be a finite set andz be a real-valued function defined on the set of subsets ofN that satisfies z(S)+z(T)≥z(S⋃T)+z(S⋂T) for allS, T inN. Such a function is called submodular. We consider the problem maxS⊂N{a(S):|S|≤K,z(S) submodular}.

Several hard combinatorial optimization problems can be posed in this framework. For example, the problem of finding a maximum weight independent set in a matroid, when the elements of the matroid are colored and the elements of the independent set can have no more thanK colors, is in this class. The uncapacitated location problem is a special case of this matroid optimization problem.

We analyze greedy and local improvement heuristics and a linear programming relaxation for this problem. Our results are worst case bounds on the quality of the approximations. For example, whenz(S) is nondecreasing andz(0) = 0, we show that a “greedy” heuristic always produces a solution whose value is at least 1 −[(K − 1)/K]K times the optimal value. This bound can be achieved for eachK and has a limiting value of (e − 1)/e, where e is the base of the natural logarithm.

Key words

Heuristics Greedy Algorithm Interchange Algorithm Linear Programming Matroid Optimization Submodular Set Functions 

Copyright information

© The Mathematical Programming Society 1978

Authors and Affiliations

  • G. L. Nemhauser
    • 1
  • L. A. Wolsey
    • 1
  • M. L. Fisher
    • 2
  1. 1.Center for Operations Research and EconometricsUniversity of LouvainLouvain-La-NeuveBelgium
  2. 2.University of PennsylvaniaPhiladelphiaUSA

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