Detecting Robust Cliques In Graphs Subject To Uncertain Edge Failures
Keywords
Conditional value-at-risk; GRASP; Heuristic; Maximum clique; Robust clique; Tabu search
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.
Publication Date
3-1-2018
Publication Title
Annals of Operations Research
Volume
262
Issue
1
Number of Pages
109-132
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/s10479-016-2161-0
Copyright Status
Unknown
Socpus ID
84961209497 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84961209497
STARS Citation
Yezerska, Oleksandra; Butenko, Sergiy; and Boginski, Vladimir L., "Detecting Robust Cliques In Graphs Subject To Uncertain Edge Failures" (2018). Scopus Export 2015-2019. 8539.
https://stars.library.ucf.edu/scopus2015/8539