Maximum matchings in sparse random graphs: Karp-Sipser revisited
Random Structures & Algorithms
Theoretical Computer Science - Phase transitions in combinatorial problems
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Introduction to Algorithms
Evolutionary Algorithms and the Maximum Matching Problem
STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Evolutionary Algorithms for Vertex Cover
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Random Structures & Algorithms
Randomized local search, evolutionary algorithms, and the minimum spanning tree problem
Theoretical Computer Science
Hybrid evolutionary algorithms on minimum vertex cover for random graphs
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Approximating covering problems by randomized search heuristics using multi-objective models
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Maximum matching in sparse random graphs
SFCS '81 Proceedings of the 22nd Annual Symposium on Foundations of Computer Science
Analyses of simple hybrid algorithms for the vertex cover problem*
Evolutionary Computation
Greedy Local Search and Vertex Cover in Sparse Random Graphs
TAMC '09 Proceedings of the 6th Annual Conference on Theory and Applications of Models of Computation
Running Time Analysis of ACO Systems for Shortest Path Problems
SLS '09 Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Hybridizing Evolutionary Algorithms with Variable-Depth Search to Overcome Local Optima
Algorithmica - Special Issue: Theory of Evolutionary Computation
Simulated annealing beats metropolis in combinatorial optimization
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Worst-case and average-case approximations by simple randomized search heuristics
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
Approximating vertex cover using edge-based representations
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Recently, various randomized search heuristics have been studied for the solution of the minimum vertex cover problem, in particular for sparse random instances according to the G(n,c/n) model, where c0 is a constant. Methods from statistical physics suggest that the problem is easy if c