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Almost optimal solutions for bin coloring problems

Mingen Lin (), Zhiyong Lin () and Jinhui Xu ()
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Mingen Lin: University at Buffalo, The State University of New York
Zhiyong Lin: University at Buffalo, The State University of New York
Jinhui Xu: University at Buffalo, The State University of New York

Journal of Combinatorial Optimization, 2008, vol. 16, issue 1, No 2, 16-27

Abstract: 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.

Keywords: Bin packing; Approximation algorithms; Online algorithms (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10878-007-9094-0

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