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.
Research supported in part by NSF ITR Award CNS-0426683 and NSF Award CNS-0626636. Part of this work was done while the author was on sabbatical at the Network Dynamics and Simulation Science Laboratory of the Virginia Bioinformatics Institute, Virginia Tech.
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Srinivasan, A. (2008). Budgeted Allocations in the Full-Information Setting. In: Goel, A., Jansen, K., Rolim, J.D.P., Rubinfeld, R. (eds) Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques. APPROX RANDOM 2008 2008. Lecture Notes in Computer Science, vol 5171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85363-3_20
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DOI: https://doi.org/10.1007/978-3-540-85363-3_20
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