On the analysis of the (1+ 1) evolutionary algorithm
Theoretical Computer Science
A Genetic Algorithm for the Capacitated Arc Routing Problem and Its Extensions
Proceedings of the EvoWorkshops on Applications of Evolutionary Computing
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PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
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STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
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Theoretical Computer Science
How mutation and selection solve long-path problems in polynomial expected time
Evolutionary Computation
Speeding up evolutionary algorithms through restricted mutation operators
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
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
IEEE Transactions on Evolutionary Computation
Biased mutation operators for subgraph-selection problems
IEEE Transactions on Evolutionary Computation
Rigorous Runtime Analysis of Inversely Fitness Proportional Mutation Rates
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Analysis of a simple evolutionary algorithm for the multiobjective shortest path problem
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Comparison of simple diversity mechanisms on plateau functions
Theoretical Computer Science
Evolutionary algorithms and dynamic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
On the effects of adding objectives to plateau functions
IEEE Transactions on Evolutionary Computation
Analysis of an asymmetric mutation operator
Evolutionary Computation
Exploring the runtime of an evolutionary algorithm for the multi-objective shortest path problem**
Evolutionary Computation
Runtime analysis of the 1-ANT ant colony optimizer
Theoretical Computer Science
Evolutionary algorithms and dynamic programming
Theoretical Computer Science
Tight analysis of the (1+1)-ea for the single source shortest path problem
Evolutionary Computation
Analysis of speedups in parallel evolutionary algorithms for combinatorial optimization
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Stochastic analysis of OneMax problem using Markov chain
Artificial Life and Robotics
Approximating vertex cover using edge-based representations
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
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Successful applications of evolutionary algorithms show that certain variation operators can lead to good solutions much faster than other ones. We examine this behavior observed in practice from a theoretical point of view and investigate the effect of an asymmetric mutation operator in evolutionary algorithms with respect to the runtime behavior. Considering the Eulerian cycle problem we present runtime bounds for evolutionary algorithms using an asymmetric operator which are much smaller than the best upper bounds for a more general one. In our analysis it turns out that a plateau which both algorithms have to cope with changes its structure in a way that allows the algorithm to obtain an improvement much faster. In addition, we present a lower bound for the general case which shows that the asymmetric operator speeds up computation by at least a linear factor.