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Solving large scale Max Cut problems via tabu search

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Abstract

In recent years many algorithms have been proposed in the literature for solving the Max-Cut problem. In this paper we report on the application of a new Tabu Search algorithm to large scale Max-cut test problems. Our method provides best known solutions for many well-known test problems of size up to 10,000 variables, although it is designed for the general unconstrained quadratic binary program (UBQP), and is not specialized in any way for the Max-Cut problem.

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Authors and Affiliations

  1. University of Colorado, Denver, CO, USA

    Gary A. Kochenberger

  2. LERIA, Universite d’Angers, 49045, Angers Cedex 01, France

    Jin-Kao Hao & Zhipeng Lü

  3. Texas A&M International University, Laredo, TX, USA

    Haibo Wang

  4. OptTek Systems, Boulder, CO, 80302, USA

    Fred Glover

Authors
  1. Gary A. Kochenberger
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  2. Jin-Kao Hao
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  3. Zhipeng Lü
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  4. Haibo Wang
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  5. Fred Glover
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Corresponding author

Correspondence to Fred Glover.

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Kochenberger, G.A., Hao, JK., Lü, Z. et al. Solving large scale Max Cut problems via tabu search. J Heuristics 19, 565–571 (2013). https://doi.org/10.1007/s10732-011-9189-8

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  • DOI: https://doi.org/10.1007/s10732-011-9189-8

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