Greedy, Prohibition, and Reactive Heuristics for Graph Partitioning
IEEE Transactions on Computers
Clique is hard to approximate within n1-
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Reactive Search and Intelligent Optimization
Reactive Search and Intelligent Optimization
Dynamic local search for the maximum clique problem
Journal of Artificial Intelligence Research
Techniques and Tools for Local Search Landscape Visualization and Analysis
SLS '09 Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Finding patterns in an unknown graph
AI Communications - The Symposium on Combinatorial Search
An adaptive multistart tabu search approach to solve the maximum clique problem
Journal of Combinatorial Optimization
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This paper presents the results of an ongoing investigation about how different algorithmic building blocks contribute to solving the maximum clique problem. We consider greedy constructions, plateau searches, and more complex schemes based on dynamic penalties and/or prohibitions, in particular the recently proposed technique of dynamic local search and the previously proposed reactive local search (RLS). We design a variation of the original RLS algorithm where the role of long-term memory (LTM) is increased (RLS-LTM). In addition, we consider in detail the effect of the low-level implementation choices on the CPU time per iteration. We present experimental results on randomly generated graphs with different statistical properties, showing the crucial effects of the implementation, the robustness of different techniques, and their empirical scalability.