Free Bits, PCPs, and Nonapproximability---Towards Tight Results
SIAM Journal on Computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Complementary Pivoting Approach to the Maximum Weight Clique Problem
SIAM Journal on Optimization
Approximation of the Stability Number of a Graph via Copositive Programming
SIAM Journal on Optimization
Global Optimization with Polynomials and the Problem of Moments
SIAM Journal on Optimization
Adaptive, Restart, Randomized Greedy Heuristics for Maximum Clique
Journal of Heuristics
Simple and Fast: Improving a Branch-And-Bound Algorithm for Maximum Clique
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
A fast algorithm for the maximum clique problem
Discrete Applied Mathematics - Sixth Twente Workshop on Graphs and Combinatorial Optimization
Solving the Maximum Clique Problem using PUBB
IPPS '98 Proceedings of the 12th. International Parallel Processing Symposium on International Parallel Processing Symposium
Variable neighborhood search for the maximum clique
Discrete Applied Mathematics - The fourth international colloquium on graphs and optimisation (GO-IV)
An effective local search for the maximum clique problem
Information Processing Letters
A hybrid heuristic for the maximum clique problem
Journal of Heuristics
A study of ACO capabilities for solving the maximum clique problem
Journal of Heuristics
A new trust region technique for the maximum weight clique problem
Discrete Applied Mathematics - Special issue: International symposium on combinatorial optimization CO'02
Dynamic local search for the maximum clique problem
Journal of Artificial Intelligence Research
Semidefinite bounds for the stability number of a graph via sums of squares of polynomials
IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
An algorithm for finding a maximum clique in a graph
Operations Research Letters
Approximating the maximum weight clique using replicator dynamics
IEEE Transactions on Neural Networks
Efficient traversal of mesh edges using adjacency primitives
ACM SIGGRAPH Asia 2008 papers
A heuristic approach for the max-min diversity problem based on max-clique
Computers and Operations Research
Extended and discretized formulations for the maximum clique problem
Computers and Operations Research
SI-CCMAC: sender initiating concurrent cooperative MAC for wireless LANs
WiOPT'09 Proceedings of the 7th international conference on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
Fast local search for the maximum independent set problem
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
Cooperating local search for the maximum clique problem
Journal of Heuristics
Local search with edge weighting and configuration checking heuristics for minimum vertex cover
Artificial Intelligence
Cliques with maximum/minimum edge neighborhood and neighborhood density
Computers and Operations Research
An exact approach for the Vertex Coloring Problem
Discrete Optimization
Subgraph extraction and metaheuristics for the maximum clique problem
Journal of Heuristics
Online search of overlapping communities
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
An adaptive multistart tabu search approach to solve the maximum clique problem
Journal of Combinatorial Optimization
NuMVC: an efficient local search algorithm for minimum vertex cover
Journal of Artificial Intelligence Research
SQBC: An efficient subgraph matching method over large and dense graphs
Information Sciences: an International Journal
Improvements to MCS algorithm for the maximum clique problem
Journal of Combinatorial Optimization
BDD-based heuristics for binary optimization
Journal of Heuristics
Speeding up branch and bound algorithms for solving the maximum clique problem
Journal of Global Optimization
Hi-index | 0.00 |
Starting from an algorithm recently proposed by Pullan and Hoos, we formulate and analyze iterated local search algorithms for the maximum clique problem. The basic components of such algorithms are a fast neighbourhood search (not based on node evaluation but on completely random selection) and simple, yet very effective, diversification techniques and restart rules. A detailed computational study is performed in order to identify strengths and weaknesses of the proposed algorithms and the role of the different components on several classes of instances. The tested algorithms are very fast and reliable: most of the DIMACS benchmark instances are solved within very short CPU times. For one of the hardest tests, a new putative optimum was discovered by one of our algorithms. Very good performances were also shown on recently proposed and more difficult instances. It is important to remark that the heuristics tested in this paper are basically parameter free (the appropriate value for the unique parameter is easily identified and was, in fact, the same value for all problem instances used in this paper).