The time complexity of maximum matching by simulated annealing
Journal of the ACM (JACM)
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
The theory of evolution strategies
The theory of evolution strategies
Drift analysis and average time complexity of evolutionary algorithms
Artificial Intelligence
The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
Towards an analytic framework for analysing the computation time of evolutionary algorithms
Artificial Intelligence
A study of drift analysis for estimating computation time of evolutionary algorithms
Natural Computing: an international journal
Journal of Computer Science and Technology
How mutation and selection solve long-path problems in polynomial expected time
Evolutionary Computation
Rigorous hitting times for binary mutations
Evolutionary Computation
Statistical distribution of the convergence time of evolutionaryalgorithms for long-path problems
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Deriving evaluation metrics for applicability of genetic algorithms to optimization problems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Identity disclosure protection: A data reconstruction approach for privacy-preserving data mining
Decision Support Systems
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This paper focuses on the computation time of evolutionary algorithms. First, some exact expressions of the mean first hitting times of general evolutionary algorithms in finite search spaces are obtained theoretically by using the properties of Markov chain. Then, by introducing drift analysis and applying Dynkin's Formula, the general upper and lower bounds of the mean first hitting times of evolutionary algorithms are given rigorously under some mild conditions. These results obtained in this paper, and the analytic methods used in this paper, are widely valid for analyzing the computation time of evolutionary algorithms in any search space(finite or infinite)as long as some simple technique processes are introduced.