Finding a maximum independent set in a permutation graph
Information Processing Letters
Theoretical Computer Science
On-line scheduling of parallel jobs with runtime restrictions
Theoretical Computer Science
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Adaptive, Restart, Randomized Greedy Heuristics for Maximum Clique
Journal of Heuristics
On places suitable for applying AI principles in NP-hard graph problems' algorithms
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Real-time systems: incomplete solution approach for the maximum-weighted clique problem
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Applying AI and incomplete solution principles to solve NP-hard problems in the real-time systems
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
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In this paper we propose collecting different maximum clique finding algorithms into a meta-algorithm, which enables to solve this NP-hard problem much more efficiently. We provide guidelines on how this intelligent meta-algorithm can be built, what information is needed from the maximum clique finding point of view and propose an elementary structure of it. Besides we review a test environment issue for the maximum clique finding area. This topic usually is undervalued, although enables to provide knowledge on algorithms behaviors and connections between algorithms and graph types, which later could be converted into the intelligent meta-algorithm's rules and definitions. We describe in this paper the test environment model, define each part of it and propose integration principles.