Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11-13, 1993
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Genetic, Iterated and Multistart Local Search for the Maximum Clique Problem
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
A fast algorithm for the maximum clique problem
Discrete Applied Mathematics - Sixth Twente Workshop on Graphs and Combinatorial Optimization
Improved Inapproximability Results for MaxClique, Chromatic Number and Approximate Graph Coloring
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
Chained Lin-Kernighan for Large Traveling Salesman Problems
INFORMS Journal on Computing
Variable neighborhood search for the maximum clique
Discrete Applied Mathematics - The fourth international colloquium on graphs and optimisation (GO-IV)
Fitness Landscapes, Memetic Algorithms, and Greedy Operators for Graph Bipartitioning
Evolutionary Computation
A hybrid heuristic for the maximum clique problem
Journal of Heuristics
Dynamic local search for the maximum clique problem
Journal of Artificial Intelligence Research
An effective local search for the maximum clique problem
Information Processing Letters
An efficient branch-and-bound algorithm for finding a maximum clique
DMTCS'03 Proceedings of the 4th international conference on Discrete mathematics and theoretical computer science
Multistart tabu search and diversification strategies for the quadratic assignment problem
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Local search with edge weighting and configuration checking heuristics for minimum vertex cover
Artificial Intelligence
NuMVC: an efficient local search algorithm for minimum vertex cover
Journal of Artificial Intelligence Research
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This paper presents a simple iterated local search metaheuristic incorporating a k-opt local search (KLS), called Iterated KLS (IKLS for short), for solving the maximum clique problem (MCP). IKLS consists of three components: LOCALSEARCH at which KLS is used, a KICK called LEC-Kick that escapes from local optima, and RESTART that occasionally diversifies the search by moving to other points in the search space. IKLS is evaluated on DIMACS benchmark graphs. The results showed that IKLS is an effective algorithm for the MCP through comparisons with multi-start KLS and state-of-the-art metaheuristics.