Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
The time complexity of maximum matching by simulated annealing
Journal of the ACM (JACM)
Fast parallel algorithms for graph matching problems
Fast parallel algorithms for graph matching problems
Maximum Matching on Boltzmann Machines
Neural Processing Letters
Finite Markov chain results in evolutionary computation: a tour d'horizon
Fundamenta Informaticae
Theory of evolutionary algorithms: a bird's eye view
Theoretical Computer Science - Special issue on evolutionary computation
Drift analysis and average time complexity of evolutionary algorithms
Artificial Intelligence
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
A new evolutionary approach to cutting stock problems with and without contiguity
Computers and Operations Research
How to analyse evolutionary algorithms
Theoretical Computer Science - Natural computing
Towards an analytic framework for analysing the computation time of evolutionary algorithms
Artificial Intelligence
An evolutionary approach to materialized views selection in a datawarehouse environment
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Statistical distribution of the convergence time of evolutionaryalgorithms for long-path problems
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Some theoretical results about the computation time of evolutionary algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Maximum cardinality matchings on trees by randomized local search
Proceedings of the 8th annual conference on Genetic and evolutionary computation
About the Time Complexity of Evolutionary Algorithms Based on Finite Search Space
Computational Intelligence and Security
Analysis of the (1 + 1)-EA for finding approximate solutions to vertex cover problems
IEEE Transactions on Evolutionary Computation
Unpacking and understanding evolutionary algorithms
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
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Most of works on the time complexity analysis of evolutionary algorithms have always focused on some artificial binary problems. The time complexity of the algorithms for combinatorial optimisation has not been well understood. This paper considers the time complexity of an evolutionary algorithm for a classical combinatorial optimisation problem, to find the maximum cardinality matching in a graph. It is shown that the evolutionary algorithm can produce a matching with nearly maximum cardinality in average polynomial time.