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Detecting robust cliques in graphs subject to uncertain edge failures

Author

Listed:
  • Oleksandra Yezerska

    (Texas A&M University)

  • Sergiy Butenko

    (Texas A&M University)

  • Vladimir L. Boginski

    (University of Florida
    University of Central Florida)

Abstract

This paper develops and compares several heuristic approaches, as well as an exact combinatorial branch-and-bound algorithm, for detecting maximum robust cliques in graphs subjected to multiple uncertain edge failures. The desired robustness properties are enforced using conditional value-at-risk measure. The proposed heuristics are adaptations of the well-known tabu search and GRASP methods, whereas the exact approach is an extension of Östergård’s algorithm for the maximum clique problem. The results of computational experiments on DIMACS graph instances are reported.

Suggested Citation

  • Oleksandra Yezerska & Sergiy Butenko & Vladimir L. Boginski, 2018. "Detecting robust cliques in graphs subject to uncertain edge failures," Annals of Operations Research, Springer, vol. 262(1), pages 109-132, March.
    • Handle: RePEc:spr:annopr:v:262:y:2018:i:1:d:10.1007_s10479-016-2161-0
    DOI: 10.1007/s10479-016-2161-0
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    References listed on IDEAS

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