Approximation Algorithms for Maximum Coverage and Max Cut with Given Sizes of Parts

  • Authors:
  • Alexander A. Ageev;Maxim Sviridenko

  • Affiliations:
  • -;-

  • Venue:
  • Proceedings of the 7th International IPCO Conference on Integer Programming and Combinatorial Optimization
  • Year:
  • 1999

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Abstract

In this paper we demonstrate a general method of designing constant-factor approximation algorithms for some discrete optimization problems with cardinality constraints. The core of the method is a simple deterministic ("pipage") procedure of rounding of linear relaxations. By using the method we design a (1-(1-1/k)k)-approximation algorithm for the maximum coverage problem where k is the maximum size of the subsets that are covered, and a 1/2-approximation algorithm for the maximum cut problem with given sizes of parts in the vertex set bipartition. The performance guarantee of the former improves on that of the well-known (1 - e-1)-greedy algorithm due to Cornuejols, Fisher and Nemhauser in each case of bounded k. The latter is, to the best of our knowledge, the first constant-factor algorithm for that version of the maximum cut problem.