Budgeted Allocations in the Full-Information Setting

  • Authors:
  • Aravind Srinivasan

  • Affiliations:
  • Dept. of Computer Science and Institute for Advanced Computer Studies, University of Maryland, College Park MD 20742

  • Venue:
  • APPROX '08 / RANDOM '08 Proceedings of the 11th international workshop, APPROX 2008, and 12th international workshop, RANDOM 2008 on Approximation, Randomization and Combinatorial Optimization: Algorithms and Techniques
  • Year:
  • 2008

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Abstract

We build on the work of Andelman & Mansour and Azar, Birnbaum, Karlin, Mathieu & Thach Nguyen to show that the full-information (i.e., offline) budgeted-allocation problem can be approximated to within 4/3: we conduct a rounding of the natural LP relaxation, for which our algorithm matches the known lower-bound on the integrality gap.