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Almost optimal solutions for bin coloring problems

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Abstract

In this paper we study two interesting bin coloring problems: Minimum Bin Coloring Problem (MinBC) and Online Maximum Bin Coloring Problem (OMaxBC), motivated from several applications in networking. For the MinBC problem, we present two near linear time approximation algorithms to achieve almost optimal solutions, i.e., no more than OPT+2 and OPT+1 respectively, where OPT is the optimal solution. For the OMaxBC problem, we first introduce a deterministic 2-competitive greedy algorithm, and then give lower bounds for any deterministic and randomized (against adaptive offline adversary) online algorithms. The lower bounds show that our deterministic algorithm achieves the best possible competitive ratio.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA

    Mingen Lin, Zhiyong Lin & Jinhui Xu

Authors
  1. Mingen Lin
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  2. Zhiyong Lin
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  3. Jinhui Xu
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Corresponding author

Correspondence to Jinhui Xu.

Additional information

The research of this paper was partially supported by an NSF CAREER award CCF-0546509.

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Lin, M., Lin, Z. & Xu, J. Almost optimal solutions for bin coloring problems. J Comb Optim 16, 16–27 (2008). https://doi.org/10.1007/s10878-007-9094-0

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  • DOI: https://doi.org/10.1007/s10878-007-9094-0

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